Skip to main content
Log in

Effectiveness and efficiency of research in Germany over time: an analysis of German business schools between 2001 and 2009

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

This article analyses the development of effectiveness and efficiency of German business schools’ research production between 2001 and 2009. The results suggest that effectiveness for most of the examined business schools increases initially. Then, however, a declining trend in the further course of time can be observed. Similar tendencies can be stated considering efficiency, even though they are slightly less pronounced. An analysis of the reasons for these observations reveals that the initial positive developments of effectiveness and of efficiency are mainly due to technology advances, whereas the following decreases are basically a result of technology backwardness. In regard to different types of business schools, a strong relation between the reputation of a school and the research effectiveness of that school becomes apparent. With reference to geographical regions, Western and Southern German business schools feature higher effectiveness than their Northern or Eastern counterparts do. This statement, however, is not valid in terms of efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. A detailed substantive analysis of the results of the mentioned studies should not be undertake here, since due to the usage of different aggregation methods and indicators as well as country-specific features, the results are not comparable with each other. However, Bolli and Farsi (2015) give a detailed description of the results of some of these studies.

  2. Although research performance data were collected for 2014 by the CHE, these data are no longer evaluated in a research performance ranking. Rather, only certain and only relative research performance data are incorporated into the so-called “Multifaceted Excellence” ranking. As the absolute data values necessary for the subsequent analyses could not be currently provided by the CHE, the data of 2014 are not integrated into the following analyses.

  3. Based on these indicators, the CHE also determines corresponding relative indicators. Because the exact CHE procedure is irrelevant for the focus of the present article, I refrain from an explicit representation and refer to the CHE publications; cf. Berghoff et al. (2011).

  4. As there is no recognised and/or clear mapping of the German federal states into north, south, east and west, I divide Germany into four approximately equal-sized areas from the geographical centre with two diagonal lines. Those federal states which are clearly in one of these entities and/or take up the largest area within an entity have accordingly been allotted to that entity.

  5. For a broader discussion of the concepts of effectiveness and efficiency, see Ahn and Dyckhoff (2004).

  6. For a short description of the idea and procedure of the basic radial DEA models, see Clermont et al. (2015). Cooper et al. (2007) give an overview of different mathematical model formulations.

  7. For an overview of alternative ranking options by means of DEA, see Hosseinzadeh Lotfi et al. (2013).

  8. For one, though older, overview of definitions and applications of the Malmquist index, see Färe et al. (1998).

  9. Basically, the location of BuSs outside the data envelopment means that such a BuS is allotted a degree of efficiency greater than 100 %. Thus, the BuS considered must reduce its outputs in order to be projected on the efficient boundary; within this context, the DEA literature discusses super efficiencies (cf. Banker et al. 1989; Andersen and Petersen 1993). Calculating super efficiency degrees is not always possible. Insolvabilities occur if a BuS cannot be projected on the efficient boundary.

  10. To determine how many and which BuSs improved and/or deteriorated in which periods with regard to their degrees of effectiveness and of efficiency, the different developments are contrasted in the two matrices of Table 9 in the “Appendix”.

  11. With regard to the effectiveness and efficiency developments (Table 9 in the “Appendix”), the inclusion of internationally visible publications has only little effect.

  12. The degrees of effectiveness and of efficiency for individual years mentioned in Table 4 relate to the effective and/or efficient boundary that is made up of the activity data from the periods 2005/08 and 2008/11. For simplicity, this will only be referred to as degrees of effectiveness and of efficiency throughout the following descriptions. In any case, the corresponding window analysis is then meant.

  13. In DEA literature, subsequent statistical investigations of the calculated degrees of effectiveness and/or of efficiency are known as two-stage DEA (Liu et al. 2013, p. 12). However, this term is not clear, because also efficiency analyses of multi-stage production processes are subsumed under this term, e.g. Cook et al. (2010).

  14. For a more detailed analysis, see Clermont and Dirksen (2016).

  15. In the datasets analysed, there are only three BuSs of private universities, but they do perform significantly better.

  16. Albers (2015), however, determines increasing returns to scale. His analyses are based on a modified database and use a varied methodological approach, which is why direct comparisons are not given here.

References

  • Agasisti, T., & Pérez-Esparrells, C. (2010). Comparing efficiency in a cross-country perspective: The case of Italian and Spanish state universities. Higher Education, 59(1), 85–103.

    Article  Google Scholar 

  • Ahn, T., Charnes, A., & Cooper, W. W. (1988). Some statistical and DEA evaluations of relative efficiencies of public and private institutions of higher learning. Socio-Economic Planning Sciences, 22(6), 259–269.

    Article  Google Scholar 

  • Ahn, H., Clermont, M., Dyckhoff, H., & Höfer-Diehl, Y. (2012). Entscheidungsanalytische Strukturierung fundamentaler Studienziele: Generische Zielhierarchie und Fallstudie. Zeitschrift für Betriebswirtschaft, 82(11), 1229–1257.

    Article  Google Scholar 

  • Ahn, H., & Dyckhoff, H. (2004). Zum Kern des Controllings: Von der Rationalitätssicherung zur Effektivitäts- und Effizienzsicherung. In E. Scherm & G. Pietsch (Eds.), Controlling: Theorien und Konzeptionen (pp. 501–525). München: Vahlen.

    Google Scholar 

  • Ahn, H., Dyckhoff, H., & Gilles, R. (2007). Datenaggregation zur Leistungsbeurteilung durch Ranking: Vergleich der CHE- und DEA-Methodik sowie Ableitung eines Kompromissansatzes. Zeitschrift für Betriebswirtschaft, 77(6), 615–643.

    Article  Google Scholar 

  • Ahn, H., & Neumann, L. (2014). Measuring effectiveness: A DEA approach under predetermined targets. International Journal of Business Analytics, 1(1), 16–28.

    Article  Google Scholar 

  • Albers, S. (2015). What drives publication productivity in German business faculties? Schmalenbach Business Review, 67(1), 6–33.

    Google Scholar 

  • Albers, S., & Bielecki, A. (2012). Wovon hängt die Leistung in Forschung und Lehre ab? Eine Analyse deutscher betriebswirtschaftlicher Fachbereiche basierend auf den Daten des Centrums für Hochschulentwicklung. http://hdl.handlenet/10419/57428. Accessed 5 January 2016.

  • Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264.

    Article  MATH  Google Scholar 

  • Asmild, M., Paradi, J. C., Aggarwall, V., & Schaffnit, C. (2004). Combining DEA window analysis with the Malmquist index approach in a study of the Canadian banking industry. Journal of Productivity Analysis, 21(1), 67–89.

    Article  Google Scholar 

  • Banker, R. D., Charnes, A. C., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.

    Article  MATH  Google Scholar 

  • Banker, R. D., Das, S., & Datar, S. M. (1989). Analysis of cost variances for management control in hospitals. Research in Governmental and Nonprofit Accounting, 5, 269–291.

    Google Scholar 

  • Barham, B. L., Foltz, J. D., & Prager, D. L. (2014). Making time for science. Research Policy, 43(1), 21–31.

    Article  Google Scholar 

  • Beerkens, M. (2013). Facts and fads in academic research management: The effect of management practices on research productivity in Australia. Research Policy, 42(9), 1679–1693.

    Article  Google Scholar 

  • Berghoff, S., Giebisch, P., Hachmeister, C.-D., Hoffmann-Kobert, B., Hennings, M., & Ziegele, F. (2011). Vielfältige Exzellenz 2011: Forschung. Anwendungsbezug, Internationalität, Studierendenorientierung im CHE Ranking, Gütersloh: CHE.

    Google Scholar 

  • Bielecki, A., & Albers, S. (2012). Eine Analyse der Forschungseffizienz deutscher betriebswirtschaftlicher Fachbereiche basierend auf den Daten des Centrums für Hochschulentwicklung (CHE). http://hdl.handle.net/10419/57429. Accessed 5 January 2016.

  • Bolli, T., & Farsi, M. (2015). The dynamics of productivity in Swiss Universities. Journal of Productivity Analysis, 44(1), 21–38.

    Article  Google Scholar 

  • Bort, S., & Schiller-Merkens, S. (2010). Publish or Perish. Zeitschrift Führung und Organisation, 79(5), 340–346.

    Google Scholar 

  • Caves, D. W., Christensen, L. R., & Erwin, W. (1982a). Multilateral comparisons of output, input, and productivity using superlative index numbers. Economic Journal, 92(1), 73–86.

    Article  Google Scholar 

  • Caves, D. W., Christensen, L. R., & Erwin, W. (1982b). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50(6), 1393–1414.

    Article  MATH  Google Scholar 

  • Charnes, A. C., Clark, C. T., Cooper, W. W., & Golany, B. (1985). A development study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces. Annals of Operations Research, 2(1), 95–112.

    Article  Google Scholar 

  • Charnes, A. C., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–441.

    Article  MathSciNet  MATH  Google Scholar 

  • Clermont, M., & Dirksen, A. (2016). The measurement, evaluation, and publication of performance in higher education: An analysis of the CHE research ranking of business schools in Germany from an accounting perspective. Public Administration Quarterly, 40(1), 133–178.

    Google Scholar 

  • Clermont, M., Dirksen, A., & Dyckhoff, H. (2015). Returns to scale of business administration research in Germany. Scientometrics, 103(2), 583–614.

    Article  Google Scholar 

  • Clermont, M., & Dyckhoff, H. (2012). Erfassung betriebswirtschaftlich relevanter Zeitschriften in Literaturdatenbanken. Betriebswirtschaftliche Forschung und Praxis, 64(3), 324–346.

    Google Scholar 

  • Clermont, M., & Schmitz, C. (2008). Erfassung betriebswirtschaftlich relevanter Zeitschriften in den ISI-Datenbanken sowie der Scopus-Datenbank. Zeitschrift für Betriebswirtschaft, 78(10), 987–1010.

    Article  Google Scholar 

  • Cook, W. D., Liang, L., & Zhu, J. (2010). Measuring performance of two-stage network structures by DEA: A review and future perspective. Omega, 38(6), 423–430.

    Article  Google Scholar 

  • Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software (2nd ed.). New York: Springer.

    MATH  Google Scholar 

  • Doyle, J. R., & Green, R. H. (1994). Efficiency and cross-efficiency in DEA: Deviations, meanings and uses. Journal of the Operational Research Society, 45(5), 567–578.

    Article  MATH  Google Scholar 

  • Dyckhoff, H., Clermont, M., Dirksen, A., & Mbock, E. (2013). Measuring balanced effectiveness and efficiency of German business schools’ research performance. Zeitschrift für Betriebswirtschaft, Special Issue, 3(2013), 39–60.

    Google Scholar 

  • Dyckhoff, H., & Gilles, R. (2004). Messung der Effektivität und Effizienz produktiver Einheiten. Zeitschrift für Betriebswirtschaft, 74(8), 765–783.

    Google Scholar 

  • Dyckhoff, H., Rassenhövel, S., & Sandfort, K. (2009). Empirische Produktionsfunktion betriebswirtschaftlicher Forschung: Eine Analyse der Daten des Centrums für Hochschulentwicklung. Zeitschrift für betriebswirtschaftliche Forschung, 61(1), 22–56.

    Article  Google Scholar 

  • Fandel, G. (2007). On the performance of universities in North Rhine-Westphalia, Germany: Government’s redistribution of funds judged using DEA efficiency measures. European Journal of Operational Research, 176(1), 521–533.

    Article  MathSciNet  MATH  Google Scholar 

  • Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity changes in Swedish pharmacies 1980–1989: A non-parametric Malmquist approach. Journal of Productivity Analysis, 3(1), 85–101.

    Article  Google Scholar 

  • Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83.

    Google Scholar 

  • Färe, R., Grosskopf, S., & Roos, P. (1998). Malmquist productivity indexes: A survey of theory and practice. In R. Färe, S. Grosskopf, & R. R. Russel (Eds.), Index numbers: Essays in honour of Sten Malmquist (pp. 127–190). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Flegg, A. T., & Allen, D. O. (2007). Does expansion cause congestion? The case of the older British Universities, 1994–2004. Education Economics, 15(1), 75–102.

    Article  Google Scholar 

  • García-Aracil, A. (2013). Understanding productivity changes in public universities: Evidence from Spain. Research Evaluation, 22, 351–368.

    Article  Google Scholar 

  • Gilles, R. (2005). Performance Measurement mittels Data Envelopment Analysis: Theoretisches Grundkonzept und universitäre Forschungsperformance als Anwendungsfall. Lohmar, Cologne: Eul.

    Google Scholar 

  • Gutierrez, M. (2007). Messung der Effizienz von Professuren mittels Data Envelopment Analysis. Zeitschrift für Betriebswirtschaft, Special Issue, 5(2007), 101–130.

    Google Scholar 

  • Hennig-Thurau, T., Walsh, G., & Schrader, U. (2004). VHB-JOURQUAL: Ein Ranking von betriebswirtschaftlich-relevanten Zeitschriften auf der Grundlage von Expertenurteilen. Zeitschrift für betriebswirtschaftliche Forschung, 56(9), 520–545.

    Article  Google Scholar 

  • Höfer-Diehl, Y. (2014). Hochschulcontrolling: Bezugsrahmen und Instrumente zur Sicherung der Lehreffektivität. Hamburg: Kovac.

    Google Scholar 

  • Horne, J., & Hu, B. (2008). Estimation of cost efficiency of Australian universities. Mathematics and Computers in Simulation, 78(2), 266–275.

    Article  MathSciNet  MATH  Google Scholar 

  • Hosseinzadeh Lotfi, F., Jahanshahloo, G. R., Khodabakshi, M., Rostamy-Malkhlifeh, M., Moghaddas, Z., & Vaez-Ghasemi, M. (2013). A review of ranking models in data envelopment analysis. Journal of Applied Mathematics, 2013.

  • Jaeger, M. (2006). Steuerung an Hochschulen durch interne Zielvereinbarungen: Aktueller Stand der Entwicklungen. Die Hochschule, 2006(2), 55–66.

    Google Scholar 

  • Johnes, J. (2006). Measuring teaching efficiency in higher education: An application of data envelopment analysis to economic graduates from UK universities 1993. European Journal of Operational Research, 174(1), 443–456.

    Article  MATH  Google Scholar 

  • Johnes, J. (2008). Efficiency and productivity change in the English Higher education sector from 1996/97 to 2004/5. The Manchester School, 76(6), 653–674.

    Article  Google Scholar 

  • Keeney, R. L. (1992). Value-focussed thinking: A path to creative decisionmaking. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Keeney, R. L., See, K. E., & von Winterfeldt, D. (2006). Evaluating academic programs: With applications to U.S. graduate decision science programs. Operations Research, 54(5), 813–828.

    Article  Google Scholar 

  • Leininger, W. (2008). Publikationsverhalten in den Wirtschaftswissenschaften. In A. von Humboldt-Stiftung (Ed.), Publikationsverhalten in unterschiedlichen wissenschaftlichen Disziplinen: Beiträge zur Beurteilung von Forschungsleistungen (pp. 39–40). Bonn: Alexander-von-Humboldt-Stiftung.

    Google Scholar 

  • Liu, J. S., Lu, L. Y. Y., Lu, W.-M., & Lin, B. J. Y. (2013). Data envelopment analysis 1978-2010: A citation-based literature survey. Omega, 41(1), 3–15.

    Article  Google Scholar 

  • Malmquist, S. (1953). Index numbers and indifference curves. Trabajos de Estatistica, 4(2), 209–242.

    Article  MathSciNet  MATH  Google Scholar 

  • Marginson, S., & van der Welde, M. (2007). To rank or to be ranked: The impact of global rankings in higher education. Journal of Studies in International Education, 11(3–4), 206–329.

    Google Scholar 

  • Olivares, M., & Schenker-Wicki, A. (2012). The dynamics of productivity in the Swiss and German University sector: A non-parametric analysis that accounts for heterogeneous production. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2139364. Accessed 5 January 2016.

  • Rassenhövel, S. (2010). Performancemessung im Hochschulbereich: Theoretische Grundlagen und empirische Befunde. Wiesbaden: Gabler.

    Book  Google Scholar 

  • Schlinghoff, A. (2002). Personalauswahl an Universitäten: Die Berufungspraxis deutscher wirtschaftswissenschaftlicher Fakultäten in den neunziger Jahren. Zeitschrift für Betriebswirtschaft, Special Issue, 2(2002), 139–147.

    Google Scholar 

  • Schrader, U., & Hennig-Thurau, T. (2009). VHB-Journal2: Methods, results, and implications of the German Academic association for business research’s journal ranking. Business Research, 2(2), 180–204.

    Article  Google Scholar 

  • Stolz, I., Hendel, D. D., & Horn, A. S. (2010). Ranking of rankings: Benchmarking twenty-five higher education ranking systems in Europe. Higher Education, 60(5), 507–528.

    Article  Google Scholar 

  • Thanassoulis, E., Kortelainen, M., Johnes, G., & Johnes, J. (2011). Costs and efficiency of higher education institutions in England: A DEA analysis. Journal of the Operational Research Society, 62(7), 1282–1297.

    Article  Google Scholar 

  • Weber, M. (1978). Economy and society: An outline of interpretive sociology. Berekley, CA: University of California Press.

    Google Scholar 

  • Weichslerbaumer, J. (2007). Hochschulinterne Steuerung über Zielvereinbarungen: Ein prozessbegleitender ökonomisch-methodischer Ansatz an der TU München. Zeitschrift für Betriebswirtschaft, Special Issue, 5(2007), 157–172.

    Google Scholar 

  • Worthington, A. C., & Lee, B. L. (2008). Efficiency, technology and productivity change in Australian universities, 1998–2003. Economics of Education Review, 27(3), 285–298.

    Article  Google Scholar 

  • Zhang, H., Patton, D., & Kenney, M. (2013). Building global-class universities: Assessing the impact of the 985 PROJECT. Research Policy, 42(3), 765–775.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marcel Clermont.

Appendix

Appendix

See Tables 6, 7, 8 and 9.

Table 6 Data of the CHE research ranking of BuSs from 2005
Table 7 Data of the CHE research ranking of BuSs from 2008
Table 8 Data of the CHE research ranking of BuSs from 2011
Table 9 Overview of the development of the effectiveness (a) and efficiency (b) in regard to individual BuSs

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Clermont, M. Effectiveness and efficiency of research in Germany over time: an analysis of German business schools between 2001 and 2009. Scientometrics 108, 1347–1381 (2016). https://doi.org/10.1007/s11192-016-2013-3

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-016-2013-3

Keywords

Navigation