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Scientometrics

, Volume 108, Issue 3, pp 1347–1381 | Cite as

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

  • Marcel ClermontEmail author
Article

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.

Keywords

Business schools Data envelopment analysis Effectiveness Efficiency Malmquist index Window analysis 
JEL Classification C67 H41 H83 I23 L31 

References

  1. 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.CrossRefGoogle Scholar
  2. 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.CrossRefGoogle Scholar
  3. 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.CrossRefGoogle Scholar
  4. 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
  5. 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.CrossRefGoogle Scholar
  6. Ahn, H., & Neumann, L. (2014). Measuring effectiveness: A DEA approach under predetermined targets. International Journal of Business Analytics, 1(1), 16–28.CrossRefGoogle Scholar
  7. Albers, S. (2015). What drives publication productivity in German business faculties? Schmalenbach Business Review, 67(1), 6–33.Google Scholar
  8. 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.
  9. Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264.CrossRefzbMATHGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. 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.CrossRefzbMATHGoogle Scholar
  12. 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
  13. Barham, B. L., Foltz, J. D., & Prager, D. L. (2014). Making time for science. Research Policy, 43(1), 21–31.CrossRefGoogle Scholar
  14. 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.CrossRefGoogle Scholar
  15. 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
  16. 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.
  17. Bolli, T., & Farsi, M. (2015). The dynamics of productivity in Swiss Universities. Journal of Productivity Analysis, 44(1), 21–38.CrossRefGoogle Scholar
  18. Bort, S., & Schiller-Merkens, S. (2010). Publish or Perish. Zeitschrift Führung und Organisation, 79(5), 340–346.Google Scholar
  19. 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.CrossRefGoogle Scholar
  20. 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.CrossRefzbMATHGoogle Scholar
  21. 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.CrossRefGoogle Scholar
  22. 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.MathSciNetCrossRefzbMATHGoogle Scholar
  23. 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
  24. Clermont, M., Dirksen, A., & Dyckhoff, H. (2015). Returns to scale of business administration research in Germany. Scientometrics, 103(2), 583–614.CrossRefGoogle Scholar
  25. Clermont, M., & Dyckhoff, H. (2012). Erfassung betriebswirtschaftlich relevanter Zeitschriften in Literaturdatenbanken. Betriebswirtschaftliche Forschung und Praxis, 64(3), 324–346.Google Scholar
  26. Clermont, M., & Schmitz, C. (2008). Erfassung betriebswirtschaftlich relevanter Zeitschriften in den ISI-Datenbanken sowie der Scopus-Datenbank. Zeitschrift für Betriebswirtschaft, 78(10), 987–1010.CrossRefGoogle Scholar
  27. 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.CrossRefGoogle Scholar
  28. 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.zbMATHGoogle Scholar
  29. 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.CrossRefzbMATHGoogle Scholar
  30. 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
  31. Dyckhoff, H., & Gilles, R. (2004). Messung der Effektivität und Effizienz produktiver Einheiten. Zeitschrift für Betriebswirtschaft, 74(8), 765–783.Google Scholar
  32. 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.CrossRefGoogle Scholar
  33. 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.MathSciNetCrossRefzbMATHGoogle Scholar
  34. 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.CrossRefGoogle Scholar
  35. 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
  36. 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.CrossRefGoogle Scholar
  37. 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.CrossRefGoogle Scholar
  38. García-Aracil, A. (2013). Understanding productivity changes in public universities: Evidence from Spain. Research Evaluation, 22, 351–368.CrossRefGoogle Scholar
  39. Gilles, R. (2005). Performance Measurement mittels Data Envelopment Analysis: Theoretisches Grundkonzept und universitäre Forschungsperformance als Anwendungsfall. Lohmar, Cologne: Eul.Google Scholar
  40. Gutierrez, M. (2007). Messung der Effizienz von Professuren mittels Data Envelopment Analysis. Zeitschrift für Betriebswirtschaft, Special Issue, 5(2007), 101–130.Google Scholar
  41. 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.CrossRefGoogle Scholar
  42. Höfer-Diehl, Y. (2014). Hochschulcontrolling: Bezugsrahmen und Instrumente zur Sicherung der Lehreffektivität. Hamburg: Kovac.Google Scholar
  43. Horne, J., & Hu, B. (2008). Estimation of cost efficiency of Australian universities. Mathematics and Computers in Simulation, 78(2), 266–275.MathSciNetCrossRefzbMATHGoogle Scholar
  44. 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.Google Scholar
  45. Jaeger, M. (2006). Steuerung an Hochschulen durch interne Zielvereinbarungen: Aktueller Stand der Entwicklungen. Die Hochschule, 2006(2), 55–66.Google Scholar
  46. 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.CrossRefzbMATHGoogle Scholar
  47. 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.CrossRefGoogle Scholar
  48. Keeney, R. L. (1992). Value-focussed thinking: A path to creative decisionmaking. Cambridge, MA: Harvard University Press.Google Scholar
  49. 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.CrossRefGoogle Scholar
  50. 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
  51. 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.CrossRefGoogle Scholar
  52. Malmquist, S. (1953). Index numbers and indifference curves. Trabajos de Estatistica, 4(2), 209–242.MathSciNetCrossRefzbMATHGoogle Scholar
  53. 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
  54. 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.
  55. Rassenhövel, S. (2010). Performancemessung im Hochschulbereich: Theoretische Grundlagen und empirische Befunde. Wiesbaden: Gabler.CrossRefGoogle Scholar
  56. 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
  57. 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.CrossRefGoogle Scholar
  58. 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.CrossRefGoogle Scholar
  59. 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.CrossRefGoogle Scholar
  60. Weber, M. (1978). Economy and society: An outline of interpretive sociology. Berekley, CA: University of California Press.Google Scholar
  61. 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
  62. 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.CrossRefGoogle Scholar
  63. Zhang, H., Patton, D., & Kenney, M. (2013). Building global-class universities: Assessing the impact of the 985 PROJECT. Research Policy, 42(3), 765–775.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2016

Authors and Affiliations

  1. 1.Institute of Management Control and Business AccountingTechnische Universität BraunschweigBrunswickGermany

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