Please use this identifier to cite or link to this item:
Year of Publication:
43rd Congress of the European Regional Science Association: "Peripheries, Centres, and Spatial Development in the New Europe", 27th - 30th August 2003, Jyväskylä, Finland
In a learning region interactions between agents strongly determine the territorial capacities to create, develop and diffuse knowledge, and finally to innovate.. More precisely, the interactive model of innovation suggests that several different pieces of knowledge have to be mixed and shared between actors in order to win the innovative race. Indeed, in our current knowledge based economies a maximum of research inputs is not a guarantee of a high level of innovation any more. On the contrary, the entities (whatever their size) which succeed to combine efficiently different and sometimes complementary or conflicting "small" pieces of knowledge inside their borders, might reach unexpected and higher level of invention and innovation. But, because of the multiple facets of knowledge (tacit, explicit, individual, collective..) and of the potential barriers generated by geographic and/or cognitive distances, these knowledge combinations or re-combinations require specific abilities or competences. First of all, firms have to develop abilities to organise internally and efficiently around innovation (we call theses competences organisational and technical ones). Besides, firms try to benefit from external innovative ideas by developing critical interfaces (Pavitt, 1998). In other words, they try and acquire competences in collaborating with customers, suppliers, but also competitors, financers and public institutions so as to reduce their mutual cognitive misunderstandings.. So, we assume that thanks to a large range of complementary competences, firms try to cope with knowledge transmission problems and to keep as innovative as possible (exploiting every external innovative ideas). Using an original (quantitative and qualitative) data base on competences for innovation (Sessi, 1997), we precisely aim at testing this hypothesis. Concretely we run an econometric model evaluating the impact of competences mastered by firms of a region, on the innovative activity (proxied by the ratio patents/GDP) of the same region. We purposely choose to run the analysis at the regional level so as to minimize the geographic distance impact. Indeed, lots of existing articles already analyse the impact of geographic proximity on innovation. We rather aim at analysing the influence of cognitive proximity. Our results allow us to highlight the core competences of innovative regions. We then build a typology of regions coupling the nature of competences a region has to master and its industrial specificities. Based on this typology we suggest some guidelines for policy makers: As regions differ in terms of industrial specificities, they also differ in the competences they have to develop and therefore differentiated innovative policies have to be run.
Appears in Collections:
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.