Does Combinatorial Knowledge Lead to a Better Innovation Performance of Firms?

Abstract The knowledge base concept in the past was often applied in its “pure form”, i.e. it was assumed that there are dominant knowledge bases in particular sectors and firms shaping knowledge and innovation processes and related networks. For “analytical sectors” such as biotech, it has been argued that codified knowledge generated by universities and R&D organizations is the key for innovation, whereas “synthetic sectors” such as machinery innovate more incrementally by recombining existing knowledge often drawn from suppliers or service firms. Empirical literature has partly confirmed these patters, but also shown more complex knowledge processes. More recently it has been argued that combinations of different knowledge bases might enhance the innovation performance of firms. For example in “analytical sectors”, firms might benefit not just from new and basic knowledge generated by research, but also from recombining existing and applied knowledge or by drawing on symbolic knowledge. Combinatorial knowledge bases might also be relevant for “synthetic” and “symbolic sectors”, but in different forms. This study investigates for the ICT sector in regions of Austria if the reliance on combinatorial knowledge leads to a better innovation performance than the use of more narrow knowledge bases.