Abstract
Universities’ role in the research system has undergone a significant change in recent years. Stand-alone strategies are continuously replaced by the pooling of resources and collaborations for knowledge. This is due to a rising complexity of scientific problems in conjunction with scarce budgets and reflects, among others, in an increasing number of co-authored papers, which are in the focus of this study.
Based on more than 125,000 articles, the paper presents general trends on the publication activities of German academia between 2000 and 2009 in a first step. Though both, the number of single- and co-authored papers increased rapidly in this period, the rising share of co-authored papers points to the growing importance of collaborations for knowledge.
Looking at co-authored papers only, local/regional and interregional/global partnerships seem to be equally important. While this is true for the whole sample, it could be assumed that the geographic distribution of partner differs with the universities’ reputation and orientation. Elite universities, for example, could be expected to publish more and more globally. Before this background the paper scrutinizes specific patterns of different types of universities in a second step.
The paper closes with an analysis of spatial proximity as a potential driver for collaborations among partners within a 1000 km circle of each university. Results are twofold. On the one hand, correlation coefficients for all considered partners confirm the generally increasing intensity of cooperation with declining distance. On the other hand, spatial proximity hardly matters for partners with a distance larger than 25 km but smaller than 475 km.
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Notes
See Feldman (1999) for a review of empirical studies and section 2 for a more in-depth discussion of the relevant literature.
A local buzz or noise (Grabher 2002) describes innovation benefits due to unintentional and serendipitous knowledge exchange which is facilitated through frequent face-to-face contacts, institutionally local embeddedness and “enhanced by shared socially constructed norms and conventions” (Feldman and Kogler 2010, p. 401). It generally refers to innovations of firms but might easily affect knowledge generation at universities as well. This is particularly true, if the local scientific community comprises several universities, public research centers and private foundations.
A critical survey on different approaches to measure knowledge spillovers is given by Nelson (2009).
Empirical findings based on the Web of Science database suggest that the universities’ performance in terms of publication records is similar to the output based on the Scopus database (Mittermaier 2011; Kowalski and Schaffer 2012). Thus, it could be carefully presumed that findings on co-authorship might be similar as well.
The sample covers almost all public universities. Private universities, which play a minor role in the German system, remain unconsidered.
There are three main counting methods, namely whole counting, fractional counting, and first author counting. Regarding whole counting, all unique countries, institutions or authors contributing to a publication get one credit. Using fractional counting, one credit is shared between the unique countries, institutions or authors with equal fractions to each participant. Last, first author counting means that one credit is given to the country to which the first author or institutional address belongs, to the institution first listed among the institutional addresses or to which the first author belongs, or to the first author (see Gauffriau et al. 2007).
Some authors are affiliated with two institutions. In this case half weight is attached to both institutions.
This is in contrast to the method of whole counting, where all unique countries, institutions or authors contributing to a publication get one credit (Schneider 2009).
The number of clusters, which equals the number of partners at the beginning, is decreased step by step according to the Ward-approach. The method is formally concluded at the point, when all partners belong to one single cluster (in this case distance corridor 0–1000 km). However, the process can be stopped earlier, before a certain level of heterogeneity, defined as sum of squared deviations, is exceeded. At this point each region belongs to one out of k cluster of partners.
We average to define the same frontier for local, regional and interregional partners for all years. However, the defined cut-off points do not reflect the exact arithmetic mean but the upper frontier of the corresponding 25 km distance corridor. This is due to the assignment of all partners into 25 km distance corridors at a later stage (see Chap. 4.3).
Indeed the DFG is very skeptical about this trend which can be explained by the authors’ salami-slicing strategy. Important results are often published step by step in relatively short articles. According the DFG, scientists have a clear incentive to do so, as the number by far outweighs the quality of articles as a push for their scientific career (Warnecke and Burchard 2010).
Three universities lost this status in 2012 after the third round but remain in the sample.
With the Technical University Munich, the University of Munich and the University of Heidelberg the so-called Elite Universities also include the only three universities listed among the best 100 universities according the Shanghai Ranking.
Collaborators within the distance of 1000 km are considered local, regional or interregional partners. Partners further away (here defined as global partners) are not considered, as spatial distance hardly matters beyond this range (Kowalski and Schaffer 2012).
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Meyborg, M., Schaffer, A. Regional and global collaborations for knowledge in German academia. Rev Reg Res 34, 157–176 (2014). https://doi.org/10.1007/s10037-014-0087-z
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DOI: https://doi.org/10.1007/s10037-014-0087-z