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.
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Notes
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.
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.
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).
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.
For a broader discussion of the concepts of effectiveness and efficiency, see Ahn and Dyckhoff (2004).
For an overview of alternative ranking options by means of DEA, see Hosseinzadeh Lotfi et al. (2013).
For one, though older, overview of definitions and applications of the Malmquist index, see Färe et al. (1998).
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.
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.
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).
For a more detailed analysis, see Clermont and Dirksen (2016).
In the datasets analysed, there are only three BuSs of private universities, but they do perform significantly better.
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.
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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
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DOI: https://doi.org/10.1007/s11192-016-2013-3