IMA/ZLW & IfU - RWTH Aachen University (GERMANY)
About this paper:
Appears in: ICERI2013 Proceedings
Publication year: 2013
Pages: 807-816
ISBN: 978-84-616-3847-5
ISSN: 2340-1095
Conference name: 6th International Conference of Education, Research and Innovation
Dates: 18-20 November, 2013
Location: Seville, Spain
In today's complex and dynamic world economy the ability of a country or a region to innovate continuously is crucial for its competitiveness. Therefore innovation constitutes a key success factor not only for enterprises, but also for countries and regions. Hence also at the regional level, innovative capability has recently been identified as a crucial determinant of social stability and economic growth (cf. Backhaus 2000).

Targeting the development and modeling of innovative capability, suitable measuring instruments at the regional level are required. Previous spatial scientific measurement approaches do not adequately consider that innovative capability substantially diverges at the regional level. To foster a country’s sustainable competitiveness, regional innovation potentials must not only be detected at an early stage, but also be systematically exploited, to finally increase the capability for innovation (cf. Brenner 2008). Existing approaches and models are built primarily to measure the innovative capability of enterprises, networks or countries (e.g. EU - Innovation Union Scoreboard, Deutsche Telekom Stiftung - Innovationsindikator). Especially with regard to a smaller scale of measuring regional innovative capability, fewer approaches are available and applicable (e.g. EU - Regional Innovation Scoreboard).

Thus, the aim of this paper is to develop a wider, regional small-scale, spatially differentiated and precise set of indicators for measuring and modeling regional innovative capability. To delineate the spatial dimension, the regional scale of the Spatial Planning Region (German: Raumordnungsregion, SPR) is being applied. SPRs are characterized by its functional definition for the measurement of regional innovative capability (cf. BBSR 2012). The contextual content dimension is given by the innovation-oriented regional development model of the Knowledge Region (KR) (cf. Fromhold-Eisebith 2009). The KR here represents an overarching, linking framework of all previously pre-established regional development models (e.g. Cluster, Innovative Mileus, Regional Innovation Systems, Learning Regions) (cf. Porter 1990, Camagni 1991, Cooke 1998, Hassink 1997). Furthermore, it provides substantive requirements for the expanded set of indicators. This is necessary for the accurate analysis of regional innovative capability.

In the focus of this paper, three approaches to measure innovative capability provide the basis for the compilation of an extended set of indicators for measuring regional innovation capability. Influenced by content and formal requirements, central as well as additional indicators are identified, which are tested on the example of the Aachen region in Germany. After testing the extended set of indicators, it becomes clear that all central as well as certain add-on indicators can be applied due to the availability of spatial regional data. Moreover, the Aachen region shows many distinct characteristics of indicators that suggest that the region is capable of innovation. As a conclusion, the functionality of the developed set of indicators has been approved and it enables a reflection of regional innovative capability.
Regional Innovative Capability, Regional Innovation, Innovative Capability, Knowledge Region, Spatial Planning Region, Aachen Region, Regional Development.