Abstract
The selection, aggregation and analysis of research performance data acquired by the Centre for Higher Education (CHE) as well as its assessment method identifying leading research business schools are controversially discussed in literature and praxis. Data Envelopment Analysis (DEA) provides an alternative method to aggregate research performance data. Thereby however, business schools can achieve high effectiveness or efficiency scores by taking into account only some and not all indicators considered as relevant, resulting in an incomplete picture of business schools’ research performance. In this paper we therefore measure and analyze a new key performance indicator, the balance score respective the specialization degree of a business school by using the new method Balanced-DEA. This indicator reflects to which extent the research performance of a business school is balanced or specialized relative to predefined virtual balanced reference points.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ahn H, Dyckhoff H, Gilles R (2007) Datenaggregation zur Leistungsbeurteilung durch Ranking: Vergleich der CHE- und DEA-Methodik sowie Ableitung eines Kompromissansatzes. Z Betriebswirt 77:615–643
Ahn H, Neumann L, Vazquez Novoa N (2012) Measuring the relative balance of DMUs. Eur J Oper Res 221:417-423 and (corrigendum) 222:68
Allen R, Athanassopoulos AD, Dyson RG, Thanassoulis E (1997) Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions. Ann Oper Res 73:13–34
Allen R, Thanassoulis E (2004) Improving envelopment in data envelopment analysis. Eur J Oper Res 154:363–379
Belton V, Stewart TJ (1999) DEA and MCDA: Competing or complementary approaches? In: Meskens N, Rouben M (eds.) Advances in Decision Analysis, Kluwer Academic Publishers, Dordrecht:87–104
Berghoff S, Federkeil G, Giebisch P, Hachmeister C-D, Müller-Böling D (2005) Das Hochschulranking: Vorgehensweise und Indikatoren. Centre for Higher Education, Working Paper 63, Gütersloh
Charnes A, Cooper WW, Rhodes EL (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429–444
Dimitrov S, Sutton W (2010) Promoting symmetric weight selection in data envelopment analysis: A penalty function approach. Eur J Oper Res 181:281–288
Dyckhoff H, Dirksen A, Mbock E (2011) Measuring the balanced efficiency of decision making units. RWTH Aachen University, School of Business and Economics, LUT-working paper, Aachen
Dyckhoff H, Mbock E, Gutgesell S (2013) Measuring key performance indicators with DEA: Balance scores and specialization degrees. RWTH Aachen University, School of Business and Economics, LUT-working paper, Aachen
Dyckhoff H, Rassenhövel S, Sandfort K (2009) Empirische Produktionsfunktion betriebswirtschaftlicher Forschung: Eine Analyse der Daten des Centrums für Hochschulentwicklung. Z Betriebswirt Forsch 61:22–56
Dyson RG, Thanassoulis E (1988) Reducing weight flexibility in data envelopment analysis. J Oper Res Soc 39:563–576
Küpper H-U, Ott R (2002) Objektivierung von Hochschul-Rankings: Analyse ihrer Meß- und Bewertungsprobleme auf der Grundlage eines Vergleichs deutscher und US-amerikanischer Rang listen. Betrieb Forsch Prax 54:614–630
Marginson S, van der Wende M (2007) To rank or to be ranked: The impact of global rankings in higher education. J Stud Int Educ 11:306–329
Tavenas F (2004) Quality assurance: A reference system for indicators and evaluation procedures. European University Association, Brussels
Thanassoulis E, Portela MCS, Despić O (2008) DEA: The Mathematical Programming Approach to Efficiency Analysis. In: Fried HO, Knox Lovell CA, Schmidt SS (eds.) The Measurement of Productive Efficiency and Productivity Growth, Oxford University Press, New York:321–340
Ursprung HW (2003) Schneewitchen im Land der Klapperschlangen: Evaluation eines Evaluators. Perspek Wirtschaftspolitik 4:177–89
Usher A, Savino M (2006) A world of difference: A global survey of university league tables. Educational Policy Institute, Canadian Education Report Series, Toronto
Weishaupt H, Preuschof C (2002) Die Bewertung der erziehungswissenschaftlichen Forschung durch das CHE. Erziehungswissenschaft 13 (25):6–17
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Gabler | Springer Fachmedien Wiesbaden
About this chapter
Cite this chapter
Dyckhoff, H., Clermont, M., Dirksen, A., Mbock, E. (2013). Measuring balanced effectiveness and efficiency of German business schools’ research performance. In: Dilger, A., Dyckhoff, H., Fandel, G. (eds) Performance Management im Hochschulbereich. ZfB-Special Issues, vol 3/2013. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-03348-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-658-03348-4_3
Publisher Name: Springer Gabler, Wiesbaden
Print ISBN: 978-3-658-03347-7
Online ISBN: 978-3-658-03348-4
eBook Packages: Business and Economics (German Language)