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Eine Analyse der Forschungseffizienz deutscher betriebswirtschaftlicher Fachbereiche basierend auf den Daten des Centrums für Hochschulentwicklung (CHE)

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  • Bielecki, Andre
  • Albers, Sönke

Abstract

Die Erstellung qualitativ hochwertiger Benchmarkings für die Forschung betriebswirtschaftlicher Fachbereiche ist von hoher praktischer Relevanz. Den Studierenden, aber auch dem wissenschaftlichen Personal und der Hochschulpolitik, wird auf diese Weise ermöglicht, die Leistungen von Fachbereichen zu vergleichen und besonders forschungsstarke Standorte zu identifizieren. Den Fachbereichen wird die Möglichkeit geboten, Verbesserungspotenziale zu identifizieren und gegebenenfalls von leistungsstärkeren Fachbereichen zu lernen. Das Centrum für Hochschulentwicklung (CHE) veröffentlicht alle drei Jahre Rankings von Hochschulen zu einzelnen Studienfächern. Hierbei werden verschiedene Leistungsindikatoren, beispielsweise zu der Anzahl und Qualität von Publikationen, den Promotionen und Habilitationen sowie den Forschungsgeldern herangezogen. Basierend auf den Daten des CHE aus dem Jahr 2008 sowie einem kürzlich veröffentlichten neuen CHE-Ranking (2011) wird in dem vorliegenden Aufsatz ein auf die Forschung der individuellen Fachbereiche bezogenes und auf die quantitativen Daten des CHE gestütztes relatives Effizienz-Benchmarking der Fachbereiche erstellt. Im Gegensatz zu einem rein Output-bezogenen Effektivitätsranking analysiert die vorliegende Effizienzanalyse die Leistungsfähigkeit der Fachbereiche bei der Transformation und Gewichtung von Forschungsinput (z.B. Professoren, Forschungsgelder und Promotionen) in Forschungsoutput (Publikationen). Je mehr Forschungsoutput mit dem gegebenen Forschungsinput erzielt wird (und vice versa), desto leistungsfähiger ist der jeweilige Fachbereich und desto höher ist sein Effizienzwert. Ein für eine solche Analyse geeignetes und in dem vorliegenden Aufsatz verwendetes Verfahren ist die Data Envelopment Analysis (DEA). Es zeigt sich, dass zwischen den Effizienzrankings der Fachbereiche keine erheblichen Unterschiede zwischen den Jahren 2008 und 2011 bestehen. Deutliche Unterschiede ergeben sich jedoch bei einem Wechsel der Leistungsindikatoren (Outputfaktoren) von nationalen zu internationalen Publikationen, die mit den Forschungsgeldern, den Promotionen und Habilitationen als Inputfaktoren erzeugt werden. Für einen Großteil der untersuchten Fachbereiche ergibt sich ferner ein erhebliches Potenzial für Steigerungen der Forschungseffizienz. Um diese zu realisieren, werden für jeden ineffizienten Fachbereich operationale individuelle Output-Ziele (Publikationsziele) und effiziente Benchmark-Fachbereiche als Orientierung vorgegeben.

Suggested Citation

  • Bielecki, Andre & Albers, Sönke, 2012. "Eine Analyse der Forschungseffizienz deutscher betriebswirtschaftlicher Fachbereiche basierend auf den Daten des Centrums für Hochschulentwicklung (CHE)," EconStor Preprints 57429, ZBW - Leibniz Information Centre for Economics.
  • Handle: RePEc:zbw:esprep:57429
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    References listed on IDEAS

    as
    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. repec:bla:germec:v:10:y:2009:i::p:352-363 is not listed on IDEAS
    3. Heinrich W. Ursprung, 2003. "Schneewittchen im Land der Klapperschlangen: Evaluation eines Evaluators," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 4(2), pages 177-190, May.
    4. 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.
    5. SIMAR , Léopold, 1995. "Aspects of Statistical Analysis in DEA-Type Frontier Models," LIDAM Discussion Papers CORE 1995061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    7. Sherman, H. David & Gold, Franklin, 1985. "Bank branch operating efficiency : Evaluation with Data Envelopment Analysis," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 297-315, June.
    8. Aly, Hassan Y, et al, 1990. "Technical, Scale, and Allocative Efficiencies in U.S. Banking: An Empirical Investigation," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 211-218, May.
    9. Carree, Martin A., 2002. "Technological inefficiency and the skewness of the error component in stochastic frontier analysis," Economics Letters, Elsevier, vol. 77(1), pages 101-107, September.
    10. Sönke Albers, 2009. "Misleading Rankings of Research in Business," German Economic Review, Verein für Socialpolitik, vol. 10(3), pages 352-363, August.
    11. Oral, Muhittin & Yolalan, Reha, 1990. "An empirical study on measuring operating efficiency and profitability of bank branches," European Journal of Operational Research, Elsevier, vol. 46(3), pages 282-294, June.
    12. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    13. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    14. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, December.
    15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. Marcel Clermont & Alexander Dirksen & Barbara Scheidt & Dirk Tunger, 2017. "Citation metrics as an additional indicator for evaluating research performance? An analysis of their correlations and validity," Business Research, Springer;German Academic Association for Business Research, vol. 10(2), pages 249-279, October.
    2. Marcel Clermont, 2016. "Effectiveness and efficiency of research in Germany over time: an analysis of German business schools between 2001 and 2009," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1347-1381, September.
    3. Heinz Ahn & Marcel Clermont & Julia Langner, 2022. "The impact of selected input and output factors on measuring research efficiency of university research fields: insights from a purpose-, field-, and method-specific perspective," Journal of Business Economics, Springer, vol. 92(8), pages 1303-1335, October.

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    More about this item

    Keywords

    Centrum für Hochschulentwicklung; Hochschulranking; Effizienzanalyse; Benchmarking; Betriebswirtschaftliche Fachbereiche;
    All these keywords.

    JEL classification:

    • M00 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General - - - General
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General

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