Skip to main content
SpringerLink
Log in

Multilevel Analysis of Industrial Clusters: Actors, Intentions and Randomness Model

  • Chapter
  • First Online:
Simulating Knowledge Dynamics in Innovation Networks

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

The literature on industrial clusters indicates a symbiotic relationship between innovation and geographical concentration of firms working in similar industries. Innovative processes require different forms of knowledge and expertise, which are distributed across individuals and organisations at different levels of industrial clusters. In this chapter, we present fundamental extensions to the SKIN model for representing such multi-level interactions. We introduce individual actors in addition to firms as agents. These agents are placed in a two-regions environment that simulates evolution of two competing regions. We also integrate elements of intentionality in addition to randomness in our model. Through subjective assessments of their managers, firms investigate and design research projects. These extensions help to open up the black box of the firm and relate firms to the creative agency of individuals in starting up new firms, establishing their research objectives and creating new knowledge. Within this broad range of issues we focus in this chapter on the role of entrepreneurship to illustrate how the extended model can be used. In experiments focusing on entrepreneurship, we generate the relative success of Silicon Valley in comparison to Boston in silico.

When an industry has thus chosen a locality for itself, it is likely to stay there long: so great are the advantages which people following the same skilled trade get from near neighbourhood to one another. The mysteries of the trade become no mysteries; but are as it were in the air, and children learn many of them unconsciously. Good work is rightly appreciated, inventions and improvements in machinery, in processes and the general organization of the business have their merits promptly discussed: if one man starts a new idea, it is taken up by others and combined with suggestions of their own; and thus it becomes the source of further new ideas. And presently subsidiary trades grow up in the neighbourhood, supplying it with implements and materials, organizing its traffic, and in many ways conducing to the economy of its material (Marshall 1920, Book IV, p 27).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ahrweiler P, Pyka A, Gilbert N (2004) Simulating knowledge dynamics in innovation networks. In: Leombruni R, Richiardi M (eds) Industry and labor dynamics: the agent-based computational economics approach. World Scientific, Singapore, pp 284–296

    Google Scholar 

  • Anselin L, Varga A, Acs Z (1997) Local geographical spillovers between university research and high technology innovations. J Urban Econ 42(3):422–448

    Article  Google Scholar 

  • Audretsch DB (1995) Innovation and industry evolution. MIT Press, Cambridge, MA

    Google Scholar 

  • Audretsch DB, Falck O, Feldman MP, Heblich S (2012) Local entrepreneurship in context. Reg Stud 46(3):379–389

    Article  Google Scholar 

  • Boero R, Castellani M, Squazzoni F (2004) Micro behavioural attitudes and macro technological adaptation in industrial districts: an agent-based prototype. J Artif Soc Soc Simulat 7(2)

    Google Scholar 

  • Boschma RA, Frenken K (2009) Some notes on institutions in evolutionary economic geography. Econ Geogr 85(2):151–158

    Article  Google Scholar 

  • Brenner T (2001) Simulating the evolution of localised industrial clusters – an identification of the basic mechanism. J Artif Soc Soc Simulat 4(3)

    Google Scholar 

  • Breschi S, Malerba F (2005) Clusters, networks and innovation. Oxford University Press, Oxford

    Google Scholar 

  • Cooke P, Morgan K (1993) The network paradigm: new departures in corporate and regional development. Environ Plann D Soc Space 11(5):543–564

    Article  Google Scholar 

  • Cooke P, Gomez Uranga M, Etxebarria G (1997) Regional innovation systems: institutional and organisational dimensions. Res Pol 26(4–5):475–491

    Article  Google Scholar 

  • Cowan R, Jonard N (2004) Network structure and the diffusion of knowledge. J Econ Dynam Contr 28(8):1557–1575

    Article  Google Scholar 

  • Cowan R, Jonard N, Zimmermann JB (2005) Bilateral collaboration and emergent networks. Available at SSRN: http://ssrn.com/abstract=882420 or http://dx.doi.org/10.2139/ssrn.882420

  • Cyert RM, March JG (1963) A behavioral theory of the firm. Prentice Hall, Englewood Cliff, NJ

    Google Scholar 

  • Doms M, Lewis E, Robb A (2010) Local labor force education, new business characteristics, and firm performance. J Urban Econ 67(1):61–77

    Article  Google Scholar 

  • Dosi G, Marengo L (1994) Toward a theory of organizational competences. In: England RW (ed) Evolutionary concepts in contemporary economics. Michigan University Press, Ann Arbor, MI, pp 157–178

    Google Scholar 

  • Feldman MP (2001) The entrepreneurial event revisited: firm formation in a regional context. Ind Corp Change 10(4):861–891

    Article  Google Scholar 

  • Feldman MP, Francis J, Bercovitz J (2005) Creating a cluster while building a firm: entrepreneurs and the formation of industrial clusters. Reg Stud 39(1):129–141

    Article  Google Scholar 

  • Fioretti G (2001) Information structure and behaviour of a textile industrial district. J Artif Soc Soc Simulat 4(4):1–30

    Google Scholar 

  • Florida R (2005) Cities and the creative class. Routledge, New York

    Google Scholar 

  • Foster J (2005) From simplistic to complex systems in economics. Camb J Econ 29(6):873–892

    Article  Google Scholar 

  • Glückler J (2007) Economic geography and the evolution of networks. J Econ Geogr 7(5):619–634

    Article  Google Scholar 

  • Hodgson GM (1998) Competence and contract in the theory of the firm. J Econ Behav Organ 35(2):179–201

    Article  Google Scholar 

  • Hofstede G (2001) Culture’s consequences – comparing values, behaviours, institutions and organizations across nations. Sage, London

    Google Scholar 

  • Holcombe RG (2003) The origins of entrepreneurial opportunities. Rev Austrian Econ 16(1):25–43

    Article  Google Scholar 

  • Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan, Ann Arbor, MI

    Google Scholar 

  • Howells J (1999) Regional systems of innovation? In: Archibugi D, Howells J, Michie J (eds) Innovation policy in a global economy. Cambridge University Press, Cambridge, pp 67–93

    Chapter  Google Scholar 

  • Jalonen H (2012) The uncertainty of innovation: a systematic review of the literature. J Manag Res 4(1):1–47

    Google Scholar 

  • Koschatzky K, Sternberg R (2000) R&D cooperation in innovation systems—some lessons from the European Regional Innovation Survey (ERIS). Eur Plann Stud 8(4):487–501

    Article  Google Scholar 

  • Krugman P (1991) Geography and trade. MIT Press, Cambridge, MA

    Google Scholar 

  • Landier A (2001) Entrepreneurship and the stigma of failure. MIT Job Market Paper

    Google Scholar 

  • Lane DA, Maxfield RR (2005) Ontological uncertainty and innovation. J Evol Econ 15(1):3–50

    Article  Google Scholar 

  • Malerba F, Orsenigo L (2000) Knowledge, innovative activities and industrial evolution. Ind Corp Change 9(2):289–314

    Article  Google Scholar 

  • March JG (1991) Exploration and exploitation in organizational learning. Organ Sci 2(1):71–87

    Article  Google Scholar 

  • Marengo L (1992) Coordination and organizational learning in the firm. J Evol Econ 2(4):313–326

    Article  Google Scholar 

  • Marengo L (1996) Structure, competence and learning in an adaptive model of the firm. In: Dosi G, Malerba F (eds) Organization and strategy in the evolution of the enterprise. Macmillan, London, pp 124–154

    Google Scholar 

  • Marshall A (1920) Principles of economics: an introductory volume. Macmillan, London

    Google Scholar 

  • Maskell P, Malmberg A (2007) Myopia, knowledge development and cluster evolution. J Econ Geogr 7(5):603–618

    Article  Google Scholar 

  • Mises L (1998 [1949]) Human action: a treatise on economics. Ludwig von Mises Institute, Auburn, AL

    Google Scholar 

  • Nelson R (1991) Why do firms differ, and how does it matter? Strat Manag J 14(S2):61–74

    Article  Google Scholar 

  • Nonaka I, Tomaya R, Nagata A (2000) A firm as a knowledge-creating entity: a new perspective on the theory of the firm. Ind Corp Change 9(1):1–20

    Article  Google Scholar 

  • Otter HS, Veen A, de Vriend HJ (2001) Location behaviour, spatial patterns, and agent-based modelling. J Artif Soc Soc Simulat 4(4)

    Google Scholar 

  • Prahalad C, Hamel G (1990) The core competence of the corporation. Harv Bus Rev 68(3):79–91

    Google Scholar 

  • Pyka A (2007) Innovation networks. In: Hanusch H, Pyka A (eds) Elgar companion to neo-Schumpeterian economics. Edward Elgar, Cheltenham

    Google Scholar 

  • Pyke F, Becattini G, Sengenberger W (eds) (1990) Industrial districts and inter-firm cooperation in Italy. International Institute for Labour Studies, Geneva

    Google Scholar 

  • Rosenberg N (2003) Innovation and economic growth. In: OECD conference on innovation and growth in tourism, Lugano, Switzerland, 18–19 Sept 2003, manuscript available at http://www.oecd.org/cfe/tourism/34267902.pdf

  • Saxenian AL (1996) Regional advantage: culture and competition in Silicon Valley and Route 128. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Schumpeter JA (1934 [1912]) The theory of economic development. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Schumpeter JA (1939) Business cycles: a theoretical, historical, and statistical analysis of the capitalist process. McGraw-Hill, New York

    Google Scholar 

  • Simon H (1976) From substantive to procedural rationality. In: Latsis SJ (ed) Method and appraisal in economics. Cambridge University Press, Cambridge

    Google Scholar 

  • Sorenson O, Audia PG (2000) The social structure of entrepreneurial activity: geographic concentration of footwear production in the United States, 1940–1989. Am J Sociol 106(2):424–462

    Article  Google Scholar 

  • Stam E (2010) Entrepreneurship, evolution and geography. In: Boschma R, Martin R (eds) The handbook of evolutionary economic geography. Edward Elgar, London, pp 307–348

    Google Scholar 

  • Sternberg R (2009) Regional dimensions of entrepreneurship. Found Trends Entrepren 5(4):211–340

    Article  Google Scholar 

  • Teece D, Pisano G, Shuen A (1997) Dynamic capabilities and strategic management. Strat Manag J 18(7):509–533

    Article  Google Scholar 

  • Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):409–410

    Article  Google Scholar 

  • Zhang J (2003) Growing silicon valley on a landscape: an agent-based approach to high-tech industrial clusters. J Evol Econ 13(5):529–548

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Research in Social Simulation (CRESS), University of Surrey, Guildford, Surrey, GU2 7XH, UK

    Ozge Dilaver

  2. British Institute at Ankara, Tahran Caddesi 24, 06700, Ankara, Turkey

    Ozge Dilaver

  3. Manchester Institute of Innovation Research (MIoIR), Manchester Business School, University of Manchester, Oxford Road, Manchester, M13 9PL, UK

    Elvira Uyarra & Mercedes Bleda

Authors
  1. Ozge Dilaver
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elvira Uyarra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mercedes Bleda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ozge Dilaver .

Editor information

Editors and Affiliations

  1. Department of Sociology Faculty of Arts and Human Sciences, University of Surrey, Guildford, Surrey, United Kingdom

    Nigel Gilbert

  2. EA European Academy of Technology and Innovation Assessment GmbH, Bad Neuenahr-Ahrweiler, Germany

    Petra Ahrweiler

  3. Lehrstuhl für Innovationsökonomik, Universität Hohenheim, Stuttgart, Germany

    Andreas Pyka

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Dilaver, O., Uyarra, E., Bleda, M. (2014). Multilevel Analysis of Industrial Clusters: Actors, Intentions and Randomness Model. In: Gilbert, N., Ahrweiler, P., Pyka, A. (eds) Simulating Knowledge Dynamics in Innovation Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43508-3_10

Download citation

Publish with us

Policies and ethics

Search

Navigation