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Innovation networks

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Abstract

This paper advances a framework for modeling the component interactions between cognitive and social aspects of scientific creativity and technological innovation. Specifically, it aims to characterize Innovation Networks; those networks that involve the interplay of people, ideas and organizations to create new, technologically feasible, commercially-realizable products, processes and organizational structures. The tri-partite framework captures networks of ideas (Concept Level), people (Individual Level) and social structures (Social-Organizational Level) and the interactions between these levels. At the concept level, new ideas are the nodes that are created and linked, kept open for further investigation or closed if solved by actors at the individual or organizational levels. At the individual level, the nodes are actors linked by shared worldviews (based on shared professional, educational, experiential backgrounds) who are the builders of the concept level. At the social-organizational level, the nodes are organizations linked by common efforts on a given project (e.g., a company–university collaboration) that by virtue of their intellectual property or rules of governance constrain the actions of individuals (at the Individual Level) or ideas (at the Concept Level). After describing this framework and its implications we paint a number of scenarios to flesh out how it can be applied.

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Notes

  1. See yellow area of Fig. 1. The most obvious candidate for a “slicing exercise” would be the biotech industry, which is the best researched in terms of its networks. However, we do not know of any study empirically investigating the conceptual networks, which led to a certain innovation, while at the same time looking at individual networks targeting the same innovation, and following the relevant inter-organisational innovation networks until successful commercialisation, all in all providing information on the dynamics on all these levels and in between them.

  2. “The IPC provides a hierarchical system of language-independent symbols for the classification of patents according to the different areas of technology to which they apply. IPC Codes of patents allow the assignment of technological fields and competences with so-called concordance tables to identify industrial sectors. In this sense, the IPC Codes can be considered as coordinates of an empirical knowledge space” (Ahrweiler et al. 2011a: 222).

References

  • Ahrweiler P (ed) (2010) Innovation in complex social systems. Routledge, London

    Google Scholar 

  • Ahrweiler P, Pyka A, Gilbert N (2011a) A new model for university–industry links in knowledge-based economies. J Prod Innovat Manag 28:218–235

    Article  Google Scholar 

  • Ahrweiler P, Gilbert N, Pyka A (2011b) Agency and structure: a social simulation of knowledge-intensive industries. Comput Math Organ Theory 17(1):59–76

    Article  Google Scholar 

  • Ahuja G (2000) Collaboration networks, structural holes, and innovation. Adm Sci Q 45:425–455

    Article  Google Scholar 

  • Albert R, Barabási A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys T4(1):47–97

    Article  Google Scholar 

  • Assimakopoulos D (2007) Technological communities and networks: triggers and drivers for innovation. Routledge, London

    Book  Google Scholar 

  • Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512

    Article  Google Scholar 

  • Beije P (1998) Technological change in the modern economy: basic topics and new developments. Elgar Publishers, Cheltenham

    Google Scholar 

  • Bozeman B, Lee S (2005) The impact of research collaboration on scientific productivity. Soc Sci Stud 35(5):673–702

    Article  Google Scholar 

  • Brass DJ, Galaskiewicz J, Greve HR, Wenpin T (2004) Taking stock of networks and organizations: a multilevel perspective. Acad Manage J 47:795–817

    Article  Google Scholar 

  • Burt RS (1992) Structural holes. Harvard University Press, Cambridge

    Google Scholar 

  • Burt RS (2004) Structural holes and good ideas. Am J Sociol 110:349–399

    Article  Google Scholar 

  • Costello FJ, Keane MT (2000) Efficient creativity: constraint guided conceptual combination. Cognit Sci 24:299–349

    Article  Google Scholar 

  • Cowan R, Jonard N, Zimmermann JB (2007) Bilateral collaboration and the emergence of innovation networks. Manage Sci 53:1051–1067

    Article  Google Scholar 

  • European Commission (2002) Benchmarking national research policies: the impact of RTD on competitiveness and employment (IRCSE). European Commission, Brussels

    Google Scholar 

  • European Commission (2008) Science, technology and innovation in Europe. European Commission, Brussels

  • Eysenck MW, Keane MT (2005) Cognitive psychology: a student’s handbook, 5th edn. Taylor Francis, London

    Google Scholar 

  • Eysenck MW, Keane MT (2010) Cognitive psychology: a student’s handbook, 6th edn. Taylor Francis, London

    Google Scholar 

  • Fagerberg J (2003) Schumpeter and the revival of evolutionary economics: an appraisal of the literature. J Evol Econ 13:125–159

    Article  Google Scholar 

  • Fagerberg J, Mowery D, Nelson RR (2006) The oxford handbook of innovation. Oxford University Press, Oxford

    Book  Google Scholar 

  • Fleming L, Marx M (2006) Managing creativity in a small world. Calif Manag Rev 48:6–27

    Article  Google Scholar 

  • Fornahl F, Brenner T (2003) Cooperation, networks and institutions in regional innovation systems. Elgar Publishers, Cheltenham

    Google Scholar 

  • Galison P (1997) Image and logic: a material culture of microphysics. The University of Chicago Press, Chicago

    Google Scholar 

  • Gibbons M, Limoges C, Nowotny H, Schwartzman S, Scott P, Trow M (1994) The new production of knowledge. The dynamics of science and research in contemporary societies. Sage, London

    Google Scholar 

  • Gloor P (2006) Swarm creativity: competitive advantage through collaborative innovation networks. Oxford University Press, Oxford

    Google Scholar 

  • Granovetter M (1973) The strength of weak ties. Am J Sociol 78:1360–1380

    Article  Google Scholar 

  • Haas P (1992) Introduction: epistemic communities and international policy coordination. Int Org 46:1–35

    Article  Google Scholar 

  • Halvey M, Keane MT, Smyth B (2006) Mobile web surfing is the same as Web surfing. Commun ACM 49:76–81

    Article  Google Scholar 

  • Imai K, Baba Y (1991) Systemic innovation and cross-border networks, transcending markets and hierarchies to create a new techno-economic system. Technology and productivity: the challenge for economic policy. OECD Publishing, Paris

    Google Scholar 

  • Keane MT (2010) Creativity: a gap analysis. In: Proceedings of international conference on cognition, experience, and creativity. IIT Gandhinagar, India

  • Keane MT, Ledgeway T, Duff S (1994) Constraints on analogical mapping: a comparison of three models. Cognit Sci 18:387–438

    Article  Google Scholar 

  • Koenig MD, Battiston S, Schweitzer F (2009) Modeling evolving innovation networks. In: Pyka A, Scharnhorst A (eds) Innovation networks: new approaches in modeling and analyzing. Springer, Berlin, pp 187–267

    Google Scholar 

  • Koschatzky K, Kulicke M, Zenker A (eds) (2001) Innovation networks: concepts and challenges in the European perspective. Springer, Heidelberg

    Google Scholar 

  • Krohn W (1995) Die Innovationschancen partizipatorischer Technikgestaltung und diskursiver Konfliktregelung. IWT-Paper 9/95, Bielefeld. The innovation chances of participatory technology shaping and discursive conflict resolution (own translation where cited)

  • Krueger J, Cantner U, Ebersberger B, Hanusch H, Pyka A (2004) Twin peaks in national income: parametric and nonparametric estimates. Rev Econ 55:1127–1144

    Google Scholar 

  • Leydesdorff L, Rotolo D, Nooy de W (2012) Innovation as a nonlinear process, the scientometric perspective, and the specification of an “Innovation Opportunities Explorer”. Digit Libr. http://arxiv.org/abs/1202.6235

  • Luhmann N (1987) Soziale Systeme. Grundriss einer allgemeinen Theorie. Suhrkamp, Frankfurt. Social systems. Foundation of a general theory (own translation where cited)

  • Lundvall BÅ (ed) (1992) National innovation systems: towards a theory of innovation and interactive learning. Pinter, London

    Google Scholar 

  • Malerba F (2002) Sectoral systems of innovation and production. Res Policy 31:247–264

    Article  Google Scholar 

  • Marquis C, Lounsbury M, Greenwood R (eds) (2011) Communities and organizations. Res Sociol Organ 33:1–363

  • Merton RK (1970) Science, technology and society in seventeenth-century England. Harper & Row, New York

    Google Scholar 

  • Nelson RR (ed) (1993) National innovation systems: a comparative analysis. University Press, Oxford

    Google Scholar 

  • Newman M (2003) The structure and function of complex networks. SIAM Rev 45:167–256

    Article  Google Scholar 

  • OECD (2009a) Policy responses to the economic Crisis: investing in innovation for long-term growth. OECD Publishing, Paris

  • OECD (2009b) Interim report on the OECD innovation strategy. OECD Publishing, Paris

  • Pastor-Satorras R, Vespignani A (2007) Evolution and structure of the internet. A statistical physics approach. Cambridge University Press, Cambridge

    Google Scholar 

  • Porter KA, Bunker-Whittington KC, Powell WW (2005) The institutional embeddedness of high-tech regions: relational foundations of the Boston biotechnology community. In: Breschi S, Malerba F (eds) Clusters, networks, and innovation. Oxford University Press, Oxford

    Google Scholar 

  • Powell WW, White DR, Koput K, Owen-Smith J (2005) Network dynamics and field evolution: the growth of inter-organizational collaboration in the life sciences. Am J Sociol 110:1132–1205

    Article  Google Scholar 

  • Pyka A, Hörlesberger M (2004) A neurological view on the technological brain of a firm. Austrian Research Centers, Mimeo

    Google Scholar 

  • Pyka A, Kueppers G (eds) (2003) Innovation networks: theory and practice. Elgar Publishers, Cheltenham

    Google Scholar 

  • Pyka A, Scharnhorst A (eds) (2009) Innovation networks. New approaches in modeling and analyzing. Springer, Berlin

  • Pyka A, Gilbert N, Ahrweiler P (2007) Simulating knowledge generation and distribution processes in innovation collaborations and networks. Cybern Syst 38:667–693

    Article  Google Scholar 

  • Schilling MA, Phelps CC (2005) Interfirm collaboration networks: the impact of small world connectivity on firm innovation. Manage Sci 53:1113–1126

    Article  Google Scholar 

  • Schumpeter J (1912) The theory of economic development. Oxford University Press, Oxford

    Google Scholar 

  • Siegel DS, Waldman D, Atwater L, Link AN (2003) Commercial knowledge transfers from universities to firms: improving the effectiveness of university–industry collaboration. J High Technol Manag Res 14:111–133

    Article  Google Scholar 

  • Smith HL, Ho K (2006) Measuring the performance of Oxford University, Oxford Brookes University and the government laboratories’ spin-off companies’. Res Policy 35:1554–1568

    Article  Google Scholar 

  • Sorenson O, Rivkin J, Fleming L (2006) Complexity, networks and knowledge flow. Res Policy 35:994–1017

    Article  Google Scholar 

  • Thursby J, Kemp S (2002) Growth and productive efficiency of university intellectual property licensing. Res Policy 31:109–124

    Article  Google Scholar 

  • Uzzi B (1997) Social structure and competition in inter-firm networks: the paradox of embeddedness. Adm Sci Q 42:35–67

    Article  Google Scholar 

  • Verspagen B, Duysters G (2004) The small worlds of strategic technology alliances. Technovation 24:563–571

    Article  Google Scholar 

  • Vos R, Rikken F (1998) Connecting dis-connected structures: the modeling of scientific discovery in medical literature databases. In: Ahrweiler P, Gilbert N (eds) Computer simulations in science and technology studies. Springer, New York, pp 91–101

    Chapter  Google Scholar 

  • Walker G, Kogut B, Shan W (1997) Social capital, structural holes and the formation of an industry network. Organ Sci 8:108–125

    Article  Google Scholar 

  • Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Watts D (1999) Small worlds. Princeton University Press, Princeton

    Google Scholar 

  • Watts D, Strogatz S (1998) Collective dynamics of “small-world” networks. Nature 393:440–442

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Innovation Research Unit (IRU), Complex Adaptive Systems Laboratory CASL, University College Dublin, 8 Belfield Office Park, Beaver Row, Clonskeagh, Dublin 4, Ireland

    Petra Ahrweiler

  2. Chair of Computer Science, University College Dublin, Dublin 4, Ireland

    Mark T. Keane

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  1. Petra Ahrweiler
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  2. Mark T. Keane
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Correspondence to Petra Ahrweiler.

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Ahrweiler, P., Keane, M.T. Innovation networks. Mind Soc 12, 73–90 (2013). https://doi.org/10.1007/s11299-013-0123-7

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