Diversité des outils et des activités de percussionà la fin du MIS 9 dans le niveau 6 d’Orgnac 3(Ardèche, France)

Layer 6 of Orgnac 3 corresponds to a cave occupation, dated to the end of MIS 9. It yielded numerous lithic and paleontological remains, and witnesses of diverse hominin activities. This paper aims to consider percussive activities from both lithic material and fauna, according to a technological and traceologicalological analysis. Knapping activities are dominant, based on the presence of hammerstones and retouchers (from bone and lithic materials). Recycling phenomena were also highlighted, with cores used as hammerstones. A flake-bulb presents also typical wear marks due to its use as retoucher (“éclat à bulbe piqueté”). These phenomena are usual during the Middle Palaeolithic and are here presented from the first stages of these lithic techno-complexes. Among the shaped pieces, a chopper bears macro-wear marks typical of use in launched percussion on a non-mineral hard material (bone?). Herbivorous remains present anthropic fractures for marrow extraction, diaphysis fragments being further punctually used as retouchers. Percussive activities have an important role in prehistoric lifeways (knapping activities, acquisition and transformation of raw materials linked to subsistence). The diversity of the percussive tool-kit testifies to a technological specialisation, while recycling shows the hominins adaptive skills to their environment.

Technological relatedness, knowledge space and smart specialisation: The case of Germany

The level of technological specialisation in the regions of Germany is assessed in this paper, as well as how such specialisation has evolved over time. Further, in three selected regions (Munich, Düsseldorf and Oberes Elbtal/Osterzgebirge), the knowledge space is explored in detail and compared to existing smart specialisation strategies. Average relatedness and knowledge space based upon EPO patent applications are used to measure the specialisation and technology trajectories of the German regions. Between three periods 1988–1992, 1998–2002 and 2008–2012, the specialisation of Germany based on EPO patent applications increased by 10%, despite a decline in many regions. Machinery and transportation industries have increased their significance. The assessment of regional smart specialisation strategies in the three German states shows that the methodology in terms of the identification of prospective industries is largely variegated and insufficiently developed. More attention should also be given to the choice of an appropriate geographical level of aggregation for analysis. Knowledge relatedness and knowledge complexity could be used as methodological tools for selecting prospective industries in smart specialisation strategies.

Implementing a smart specialisation strategy: an evidence-based approach

Smart specialisation is now a major idea behind the European Commission’s cohesion policy reforms in the field of innovation, and it must be applied by European Union member countries in order to secure funding under the 2014–2020 European Union budget, even though the concept itself has only recently emerged. The success of translating this policy into practice depends on a thorough analysis of regions’ and countries’ potential for innovation based on empirical evidence. Currently, countries use a wide array of methods to define priority areas, but these have, for the most part, failed to address the challenges of this process. This article explores the data that can be used in the prioritisation process of developing a smart specialisation strategy. The approach follows the main recommendations for profiling regions and countries, uses data already available at the national statistical offices, and is based on indicators that can be grasped intuitively by policymakers. It includes data on each relevant aspect of smart specialisation, that is, economic, scientific and technological specialisation, as well as the entrepreneurial discovery process. This article demonstrates the approach using a case with Slovenian data; the results suggest that it can be an effective tool for narrowing down a list of industries to be considered for a smart specialisation strategy. Points for practitioners A smart specialisation strategy will be a precondition for using European Union regional and investment funds during 2014–2020 in order to support research and innovation investments. The success of translating this policy into practice depends on a thorough analysis of regions’ and countries’ potential for innovation based on empirical evidence. A ready-to-use methodology for narrowing down a list of industries to be considered for a smart specialisation strategy is proposed, and is demonstrated using the example of Slovenia.