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Agency and structure: a social simulation of knowledge-intensive industries

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Abstract

Modern knowledge-intensive economies are complex social systems where intertwining factors are responsible for the shaping of emerging industries: the self-organising interaction patterns and strategies of the individual actors (an agency-oriented pattern) and the institutional frameworks of different innovation systems (a structure-oriented pattern). In this paper, we examine the relative primacy of the two patterns in the development of innovation networks, and find that both are important. In order to investigate the relative significance of strategic decision making by innovation network actors and the roles played by national institutional settings, we use an agent-based model of knowledge-intensive innovation networks, SKIN. We experiment with the simulation of different actor strategies and different access conditions to capital in order to study the resulting effects on innovation performance and size of the industry. Our analysis suggests that actors are able to compensate for structural limitations through strategic collaborations. The implications for public policy are outlined.

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References

  • Amable B (2003) The diversity of modern capitalism. Oxford University Press, Oxford

    Book  Google Scholar 

  • Argyris C, Schoen DA (1996) Organisational learning: a theory of action perspective. Addison-Wesley, Reading

    Google Scholar 

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

    Google Scholar 

  • Bolton GE, Katoka E, Ockenfels A (2005) Cooperation among strangers with limited information about reputation. J Public Econ 89:1457–1468

    Article  Google Scholar 

  • Bourdieu P (2005) The social structures of the economy. Polity Press, Cambridge

    Google Scholar 

  • Bourdieu P (1992) The logic of fields. In: Bourdieu P, Wacquant L (eds) An invitation to reflexive sociology. University of Chicago Press, Chicago, pp 94–114

    Google Scholar 

  • Brusoni S, Prencipe A, Pavitt K (2001) Knowledge specialisation, organizational coupling and the boundaries of the firm: why firms know more than they make? Adm Sci Q 46:597–621

    Article  Google Scholar 

  • Cantner U, Pyka A (1998) Absorbing technological spillovers. Simulations in an evolutionary framework. Ind Corp Change 7(2):369–397

    Google Scholar 

  • Cohen WM, Levinthal D (1989) Innovation and learning: the two faces of R&D. Econ J 99:569–596

    Article  Google Scholar 

  • Casper S, Kettler H (2001) National institutional frameworks and the hybridization of entrepreneurial business models: the German and UK biotechnology sectors. Ind Innov 8:5–30

    Article  Google Scholar 

  • Casper S, van Waarden F (2006) Innovation and institutions. A multi-disciplinary review of the study of innovation systems. Elgar, Cheltenham

    Google Scholar 

  • Collins HM (1995) Science studies and machine intelligence. In: Jasanoff S, Markle GE, Petersen JC, Pinch T (eds) Handbook of science and technology studies. Sage, Thousand Oaks, pp 286–301

    Google Scholar 

  • Commission of the European Communities (2002) Benchmarking national R&D policies: first results. Commission Staff Working Paper, Brussels SEC 129

  • Cooke P, Morgan K (1998) The associational economy, firms, regions and innovation. Oxford University Press, Oxford

    Google Scholar 

  • de Geus A (1997) The living company. Brealy, London

    Google Scholar 

  • Dewey J (1938) Experience and education. Collier, New York

    Google Scholar 

  • Duncan RB (1974) Modifications in decision structure in adapting to the environment: some implications for organizational learning. Decis Sci 5:705–725

    Article  Google Scholar 

  • Eliasson G (1995) General purpose technologies, industrial competence and economic growth. Working Paper, Royal Institute of Technology, Stockholm

  • Feldman M, Francis J, Bercovitz J (2005) Creating a cluster while building a firm: entrepreneurs and the formation of industry clusters. Reg Sci 39:129–142

    Article  Google Scholar 

  • Garcia R, Dunn DT, Smith LA (forthcoming a) Boundary spanners and social networks surrounding research centers. NSF 04-556 Partners for Innovation Program. Working Paper

  • Garcia R, Dunn DT, Smith LA (forthcoming b) Performance of knowledge interactions between public research centres and industrial firms: an application for Spanish public research centres based on project-level data. Working Paper

  • Granovetter M (1985) Economic action and social structure: the problem of embeddedness. Am J Soc 91:481–510

    Article  Google Scholar 

  • Hall P, Soskice D (eds) (2001) Varieties of capitalism. Oxford University Press, Oxford

    Google Scholar 

  • Hedberg B (1981) B. Hedberg, How organizations learn and unlearn. In: Nystrom PC, Starbuck WH (eds) Handbook of organizational design. Oxford University Press, Oxford

    Google Scholar 

  • Knight FH (1921) Risk, uncertainty and profit. Chicago

  • Lisbon Agenda Group (2007): http://www.mariajoaorodrigues.eu/lisbon-agenda/group/

  • Malerba F, Nelson R, Orsenigo L, Winter S (1999) History friendly models of industry evolution: the computer industry. Ind Corp Change 8:3–40

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Michael DM (1973) On learning to plan and planning to learn. Jossey-Bass, Hoboken

    Google Scholar 

  • Michelet R (1992) Forming successful strategic marketing alliances in Europe. J Eur Bus 4:11–15

    Google Scholar 

  • Pavitt K (1987) The objectives of technology policy. Sci Public Policy 14:182–188. Reprinted in Pavitt (1999)

    Google Scholar 

  • Petit P, Amable B (2001) The diversity of social systems of innovation and production during the 1990s. Working Paper CEPREMAP # 2001 – 15

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

    Article  Google Scholar 

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

    Google Scholar 

  • Pyka A, Saviotti PP (2003) Innovation networks in the biotechnology-based industries. In: Pyka A, Kueppers G (eds) Innovation networks - theory and practice. Edward Elgar, Cheltenham, pp 75–107

    Google Scholar 

  • Pyka A, Saviotti PP (2005) The Evolution of R&D networking in the biotech industries. Int J Entrepreneurship Innov Manag 5(1/2):49–68

    Google Scholar 

  • Weber M (2003) Innovation networks and the transformation of large socio-technical systems: the case of combined heat and power technology. In: Pyka A, Kueppers G (eds) Innovation Networks - Theory and Practice. Edward Elgar, Cheltenham, pp 133–165

    Google Scholar 

  • Windrum P (2003) The role of knowledge-intensive business services (KIBS) in e-commerce. In: Pyka A, Kueppers G (eds) Innovation networks - theory and practice. Edward Elgar, Cheltenham, pp 108–132

    Google Scholar 

  • Winter SG (1984) Schumpeterian competition in alternative technological regimes. J Econ Behav Organ 5:237–261

    Article  Google Scholar 

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Authors and Affiliations

  1. UCD Innovation Research Unit IRU, CASL, University College Dublin, Dublin, Ireland

    Petra Ahrweiler

  2. Centre for Research in Social Simulation, University of Surrey, Guildford, Surrey, UK

    Nigel Gilbert

  3. Economics Department, University of Hohenheim, Stuttgart, Germany

    Andreas Pyka

Authors
  1. Petra Ahrweiler
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  2. Nigel Gilbert
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  3. Andreas Pyka
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Corresponding author

Correspondence to Petra Ahrweiler.

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Ahrweiler, P., Gilbert, N. & Pyka, A. Agency and structure: a social simulation of knowledge-intensive industries. Comput Math Organ Theory 17, 59–76 (2011). https://doi.org/10.1007/s10588-010-9081-3

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  • DOI: https://doi.org/10.1007/s10588-010-9081-3

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