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The role of German universities in a system of joint knowledge generation and innovation

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Mirja Meyborg

1. Introduction

Texte intégral

"Knowledge is power"
Francis Bacon (1597)

1As it is shown by the statement of Francis Bacon from the 16th century, it is not a new phenomenon that knowledge is regarded as one of the key resources to an economy in order to bring up new technologies and innovations. At that time, Francis Bacon still wrote about his ambition to bring the human being on a higher level of existence through the power of knowledge. However, it is not surprising that many scholars referred to Francis Bacon's statement, and further showed that the accumulation of human capital is the most strategic resource for regional economic development and competitiveness within our globalised world (Romer 1986, Lucas 1988, Grossman and Helpman 1991, Lundvall 1992, Becker 1994 and Romer 1996). Further, the relation between knowledge and innovation is self-evident as knowledge is widely seen as a crucial factor for innovation activity, so that innovation can be seen as the result of an interactive process of knowledge generation, diffusion and application. Thus, the expedient exploration of knowledge is essential for shaping successful innovations (Camagni 2001 and Katila and Ahuja 2002).

1.1. Universities in the Concept of Knowledge Generation and Innovation

2A vast majority of nowadays literature confirms that in times of globalization universities have increasingly become involved in economic development and are often believed to play a key role in regional economic development as well as in gaining new technologies and innovations (Etzkowitz 1989, Etzkowitz and Leydesdorff 2000, Miner et al. 2002). Besides, the traditional university whose primary objective is research and teaching has been highly complemented by increasingly 'entrepreneurial university' which generates revenue and enhances its political viability through technology transfer and the commercial transfer of innovation. In this context, the famous cases of Stanford University and Massachusetts Institute of Technology (MIT) are often mentioned as they played crucial roles in the development of Silicon Valley and the greater Boston area (Etzkowitz 1989 and Etzkowitz and Leydesdorff 2000). Hence, the fully developed industrialized economies are undergoing important and fundamental economic and social changes, as, for example, pictured through substantial increases of the share of the total resources devoted to research and development (R&D) or changes in the educational achievements of the labour force. In this context, it is not surprising that the German academic landscape has become an ever more important issue as it plays an essential role regarding the creation of high potentials that are, in turn, responsible for developing, using and diffusing knowledge and technology. Being aware of the importance of new knowledge and innovation, it is further important to tackle the question how both can be developed and dispersed best. Already Lucas (1988) and Grossman and Helpman (1991) have shown that knowledge diffusion between actors within an institutional system is crucial for innovation and economic growth. Following Breschi and Lissoni (2001), those knowledge-based spillovers are not 'in the air', as they are the result of intended interaction between any social actors that simultaneously help to realise the innovation itself. Thus, knowledge generation and innovation is the result of a complex set of relationships among actors in a system, which can include enterprises, universities, research institutes and the government (OECD 1997).

1.2. Objectives

3Following the introductory words, it is beyond question that the ability to create, access and use knowledge and technology has become a fundamental determinant of long-term development and competitiveness. Despite a growing importance of public research centers and private think-tanks, it is the universities who have increasingly become involved in economic development and are often believed to play a crucial role for regional economic growth rates. This PhD thesis exactly picks up this line of thought and explores the role of the German universities in a system of joint knowledge generation and innovation and applies a broad social network analysis (SNA) of publications and patents with a special focus on the spatial dimension. The aim of this work is to provide new insight into the behavioural patterns of the German universities regarding their knowledge generation, innovation and collaboration function. Thereby, it is of high interest how they have developed over the past ten years and to what extent academic knowledge transfer has become important especially to industry and of course to the broader research community. In this context, it is also asked whether the importance of the spatial factor has changed over time. Finally, this PhD thesis aims to provide appropriate policy recommendations which are closely tailored to the requirements of the German universities as well as to the needs of the whole German knowledge-based community in order to be able to tackle future challenges.

1.3. Basic Research Line and Structure

  • 1 The terms group and type are used interchangeable within the course of this PhD thesis.

4In order to achieve the objectives drawn above, the basic research line is set as follows. First of all, it is pointed to the highly increasing activity of the German universities regarding their publication and patenting behaviour as well as to their growing collaboration potential. Second, it is analysed whether the role of the German universities has changed from solely knowledge producers towards knowledge mediators, which leads to an increasing importance of universities as a central node for knowledge and innovation transfer. Third, this PhD thesis tackles the question whether geographic distance still plays an important role regarding close network collaborations as already discussed before. Fourth, three different groups1 of German universities are explored and compared with each other regarding their knowledge generation, innovation and collaboration behaviour. Overall, the empirical findings are based on publications of the Scopus database and enclose several thousand publications for each university for a time period from 2000 until 2009. Besides, the EPO Worldwide Patent Statistical Database Version October 2010 (PATSTAT) is used, in order to measure innovation activities radiating from all German universities for the same time period.

5However, in order to achieve a detailed overview regarding the role and behaviour of the German universities within their particular systems of knowledge generation, innovation and collaboration as described above, this PhD thesis utilizes the following structure:

Figure 1: Structure of the PhD Thesis (own illustration).

6As can be seen from the figure, this PhD thesis starts with the theoretical background and elaborates upon the concept of knowledge and innovation. Thereby, it offers a short definition of knowledge and shortly discusses the nature and concept of knowledge, as it is a driving force for innovation activity. Afterwards, the concept of innovation is illustrated through the illustration of different innovation systems, through several measures of innovation activity as well as through the relevance of innovations for an economy. Finally, the increasing importance of innovation networks is stressed followed by a short introduction of proximity patterns in times of globalization.

7After elaborating upon the reasons why knowledge, innovation and collaboration are essential for economies that have experienced a fast expansion of knowledge-based industries and activities which basic raw material is simply new knowledge, chapter three is based upon the role of universities within knowledge and innovations networks. As already discussed, universities are seen as a source of knowledge intensive capital which is further beneficial for technological change, innovation and economic growth. This chapter illustrates an overview of university research in Germany, and simultaneously shows several support measures with regard to university interactions. It finally demonstrates the impact of university research as important driving force for regional economic development and competitiveness as well as several possible types of university interactions.

8Chapter four illustrates the data of analysis as well as the subject of study. Thus, it presents a detailed introduction of both innovation indicators, namely scientific publications and patent applications that are used throughout the work. In this context, it also points to the scope of each data set, emphasizing that it can make use of around 250,000 papers where at least one German univeristy has been involved with over the past ten years. It finally introduces the German universities that are considered and offers a classification of the three different types of univeristies that are to be explored and compared with each other.

  • 2 See chapter six for detailed information on this topic.

9While chapter five is based upon the concept of the SNA, the subsequent chapter elaborates upon the concept of the spatial analysis. First of all, it is shown in how far the instrument of SNA is generally used and how it is applied in the context of scientific publications and patent applications. Thus, several centrality measures are introduced which help to identifiy the particular behaviour of the German universities regarding their knowledge, innovation and collaboration potential. Within the concept of the spatial analysis, it is shown how this PhD thesis deals with proximity patterns. In order to be able to provide appropriate answers on this topic, it is compulsive to be aware of all distances, measured in kilometres, which are to be covered between the German universities and their individual cooperation partners. Thereby, the ascertainment of the exact geographical position of each co-author has been calculated by the Haversine formula2.

10In order to give insight into role of the German universities in a system of joint knowledge generation and innovation, chapter seven illustrates all relevant hypotheses in this regard and simultaneously indicates the statistical tools that have been used to underline the results. The empirical results are further displayed in the subsequent chapter. Thereby, a broad overview of the overall publication and patenting activity of all German universities over the past ten years is firstly illustrated. It is shown how the role of the German universities has changed towards knowledge mediators, hence, indicating that cooperation patterns have become much more important over the past decade. In this context, the institutional distribution of the German university cooperation partners is also illustrated and points to the most famous university-university linkages, but also highlights the emerging collaborations between universities and enterprises regarding scientific publications. Those university-industry linkages are evident for the patent analysis and are also highlighted in this regard. A second cornerstone consists of an extensive spatial distribution measure which illustrates whether distance patterns still matter within the German university knowledge networks as it did years before.

11Chapter nine introduces the hypotheses and methodology considering the different types of German universities, distinguishing between elite, medical and technical universities, while chapter ten further provides the empirical results in this regard. Here, it is shown how the different types of German universities behave regarding their individual knowledge, innovation and collaboration potential. Of course, proximity patterns in times of globalisation are again of high interest.

12As significant differences have generally been discovered between the different types of German universities, chapter eleven presents a case study and explores the differences between the Karlsruhe Institute of Technology which is a technically oriented university and the University of Heidelberg which is medically oriented. These two universities have been selected as main differences have been discovered between technical and medical universities, and it is thus aimed to further confirm the empirical results of the previous chapters.

13Finally, chapter twelve provides the final conclusion of this work with an overall reflection of the empirical results. Thereby, it offers policy recommendations and delivers simultaneously evidence for further research on this topic.

Notes

1 The terms group and type are used interchangeable within the course of this PhD thesis.

2 See chapter six for detailed information on this topic.

Table des illustrations

Légende Figure 1: Structure of the PhD Thesis (own illustration).
URL http://books.openedition.org/ksp/docannexe/image/231/img-1.jpg
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