Evaluating social science and humanities knowledge production: an exploratory analysis of dynamics in science systems

P. van Hemert, Peter Nijkamp and J. Verbraak
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P. van Hemert: Vrije Universiteit Amsterdam, Faculteit der Economische Wetenschappen en Econometrie (Free University Amsterdam, Faculty of Economics Sciences, Business Administration and Economitrics

No 13, Serie Research Memoranda from VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics

Abstract: Knowledge is gaining increasing importance in modern-day society as a factor of production and, ultimately, growth. This paper explores the dynamics in university knowledge production and its effect on the state of university-industry-policy exchange in the Netherlands. Science systems are said to be in transformation. The university has evolved from performing conventional research and education functions to serving as an innovation-promoting knowledge hub; dynamics that have received mixed reactions. Social Sciences and Humanities (SSH) assume a special position, insofar that their focus seems primarily on conventional research and education functions, and not directly on (commercial) valorisation. Societal changes are, however, pressing for a reconsideration of the role of SSH. In our paper we distinguish between three important new movements that seem to affect SSH. It is believed that these movements that already have some impact today will considerably influence SSH in the future. These developments are: further differentiation, synthesis between the various sub-disciplines of SSH and natural sciences, and shifts in paradigms. The aims of this paper are twofold: 1) assess what is believed to be a most likely development of SSH by means of discovery of relevant subsets of factors influencing university knowledge production; and 2) discover whether the knowledge production factors show characteristics of a general development similarly to the ‘Mode 2’ concept introduced by Gibbons et al. (1994). By means of 22 semi-structured personal interviews with key representatives from the business, university and the policy sector, a systematic qualitative database was created. Our explanatory framework employs an artificial intelligence method, viz. rough set analysis. On the basis of these results, we find that a small minority of the respondents prefers a closer relationship of SSH with society, government and industry,

Keywords: science systems; knowledge production; Mode 2; SSH; rough set analysis; artificial intelligence (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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