Seminar: Innovation Networks - ENTFÄLLT
Instructors: Prof. Dr. Petra Ahrweiler; Blanca Luque CapellasShortname: S Techniksoziologie
Course No.: 02.149.16911
Course Type: Seminar
Recommended reading list
Ahrweiler, P. (ed.) (2010): Innovation in complex social Systems, London: RoutledgeContents
Description:Innovation policymakers, business managers and the public often expect that the current investments in R&D, higher education institutions, science-industry networks etc. will immediately produce a flow of products and processes with high commercial returns. The disappointments and legitimatory problems arising from missing outputs are considerable and show the limits of steering, control and policy functions. If not a principle apprehension against the importance of knowledge and innovation, the responsible innovation managers mention a frustration with the too messy and complicated features of the innovation process, which simply “does not seem to compute”. Innovation, the creation of new, technologically feasible, commercially realisable products and processes, is – if things go right - emerging from an ongoing interaction process of innovative organisations in various sectors such as universities, research institutes, firms, government agencies, venture capitalists and others. These actors generate and exchange knowledge, financial capital, and other resources in networks of relationships, which are embedded in institutional frameworks on the local, regional, national and international level. Innovation is an emergent property from these interactions on the micro level – if the combination of actors and organisations, their compatible capabilities, and their cooperative behaviours match. No equation will predict this match or warn from a mismatch beforehand.
This seminar now has something new to say about innovation. It will introduce into cutting-edge methods coming from the natural sciences, from computer science, and mathematics to deal with the complex aspects of socio-economic innovation processes - and this without leaving out the messy features of empirical reality and the „human element“, but indeed taking full account of it. The conceptual framework opens up a new paradigm for innovation research, which is announced by its title: the sessions analyse innovation in networks while making innovation understandable and tractable using tools such as computational network analysis and agent-based simulation.
Learning outcomes:
This course comprises programmatic contributions of the leading international experts of innovation research and discusses issues of immediate concern to innovation policy makers and innovation business managers. On the theoretical side, it will provide systematic knowledge on the nature and characteristics of innovation processes to keep up with the complexity, with the non-linearities and the self-organising features of innovation performance. With this, it will further demonstrate the embeddedness of socio-economic innovation research in complexity science and computational approaches.
On the practical side, it will identify points of intervention and support for innovation and for collaborative networking with partners and stakeholders.
The course introduces the state of the art in international Innovation Research
- by presenting results from the empirical analysis of innovative actors such as universities, SMEs, and MNEs while focusing on their respective contributions to the innovation process,
- by illuminating the systemic context of innovation with emphasis on national and sectoral systems of innovation in an evolutionary frame
- and by discussing the tools and methods with which innovation networks in complex social systems can be successfully investigated to extend and apply our knowledge of them most effectively.