Innovation networks for regional development

Innovation, for long recognized as the engine of economic growth, is increasingly considered as the driving force for regional development and to a large part responsible for disparities in income development. It seems not unlikely that even successful regional clusters might finally dissolve following a cul-de-sac technological trajectory. Thus, we expect that a region`s composition in terms of industrial sectors - at different stages of the industry life cycle - affects deeply the ability to develop new growth opportunities. In recent years, innovation networks have been recognized as a persistent organizational phenomenon in industrial innovation, and evolutionary economic theory considers them fundamentally as the locus where new knowledge is created. Consequently, innovation networks are considered as an effective target as well as a tool for regional innovation policy. However, the process of how networks of innovating organizations contribute to regional development and structural change is very complex and is so far underinvestigated by economic research. The proposed project adopts agent-based modelling as a new methodological approach to address the missing micro-macro link in the context of regional innovation. The main objective of the project is to build a comprehensive model of how organizations - firms, public research organizations and other relevant organizations - create and exchange knowledge in a concrete regional setting, how they form innovation networks, and how they contribute to successful and sustainable innovation. This is achieved by establishing a computational laboratory for comparative analysis of innovation dynamics in geographical space, enabling for the first time the application of agent-based models of innovation networks to specific regions and sectors. Simulation experiments for various sectors will be performed in selected regions, namely in a classical "high-tech region" (Stuttgart, Germany) and a "metropolitan knowledge intensive services region" (Vienna, Austria). The significance of the proposed research is to be seen in the advancement of theories of regional innovation based on micro-processes, and the improvement of agent-based simulation methodology in the regional innovation context. Fine-grained and thorough empirical calibration and validation of such models will improve the credibility of simulation methods both in the scientific and the policy context. Beyond scientific progress, the expected impacts of this project are related with improved ex-ante assessment of regional development and corresponding policy measures.

Innovation, for long recognized as the engine of economic growth, is increasingly considered also as the driving force for regional development. Concepts like the technology clusters have been successfully adopted by regional as well as research, technology and innovation policy. However, facing an increasingly dynamic technological development, even successful regional clusters might finally dissolve if they find themselves in a cul-de-sac technological trajectory. In recent years, innovation networks have become a persistent organizational phenomenon in industrial innovation, and evolutionary economic theory considers them fundamentally as the locus where new knowledge is created. Consequently, innovation networks could work as an effective policy tool for supporting and maintaining the innovation performance of regions. However, the process of how networks of innovating organizations contribute to regional development and structural change is very complex and is so far under-investigated by economic research. The main objective of the project was to build an agent-based model (ABM) of regional knowledge production. Organizationsfirms, public research organizations and other relevant organizationscreate and exchange knowledge in a concrete regional setting, they form innovation networks, and with direct as well as indirect interactions they contribute to successful innovation at the region level. Thus, a computational laboratory for comparative analysis of innovation dynamics in geographical space is provided, enabling for the first time the application of empirically grounded ABMs of innovation systems referring to specific regions and sectors. Simulation experiments were performed in selected regions, namely in a classical high-tech region (Stuttgart, Germany) and a metropolitan knowledge intensive services region (Vienna, Austria). The projects scientific achievements are both in the advancement of theory (models of regional innovation based on micro-processes) and in the improvement of methodology (empirical calibration of ABMs). Beyond scientific progress, fine-grained and thorough empirical validation of the models has also improved the credibility of simulation methods in the policy context: It has been demonstrated that simulation methods are able to support the ex-ante assessment of policy strategies and measures a challenge that research, technology and innovation policy is increasingly facing.