Abstract
This chapter addresses how micro-level preferences and decisions about collaboration made by a large number of heterogeneous firms can affect the macro-level evolution of inter-firm networks and the structure of industrial knowledge bases. We conduct the analysis by way of an agent-based model (ABM) that mimics key stylized facts about firm-level business strategies and innovation networking in the Nordic internet service provider (ISP) industry.
To develop the model, we make use of an existing ABM—Simulating Knowledge Dynamics in Innovation Networks (SKIN) and to visualize the results we use the social network analysis software Gephi. As a means of improving the empirical validity of the model, we iteratively presented and modified the model through a sequence of discussions with strategic analysts at Telenor, a large Norwegian internet service provider.
The paper suggests that the adoption by many firms of a collaboration-oriented and explorative innovation strategy facilitates the evolution of a densely connected regional network in which the participant firms gradually build complex but increasingly similar knowledge bases. By contrast, the adoption by many firms of more internally oriented and exploitative innovation strategies facilitates the emergence of less densely connected networks in which the knowledge bases of the firms are less complex and more heterogeneous. This latter outcome appears to have more beneficial implications for the competitive performance of smaller specialized firms, and for the novelty-generation potential of the industry as a whole.
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Notes
- 1.
The Réseaux IP Européens Network Coordination Centre (RIPE) is the Regional Internet Registry (RIR) for Europe. As a RIR, RIPE oversees the allocation and registration of Autonomous System (AS) Numbers) in European countries. This is relevant in the context of our study since firms need AS numbers in order to independently sell Internet access capacity, and thus operate as ISPs. On RIPEs website (http://www.ripe.net/), there is a publicly available database of organizations with AS numbers that operate in the Nordic countries.
- 2.
These are Statistics Norway, Statistics Finland, Statistics Denmark and Statistics Sweden.
- 3.
An autonomous system is one Internet protocol (IP) network or sets of networks under a single administrative control. Companies and organizations might own more than one autonomous system, but the idea is that each autonomous system is managed independently. Autonomous System Numbers (ASNs) are globally unique numbers that are used to identify autonomous systems (ASes) and which enable an organization to route its own Internet traffic and to trade Internet access capacity. ASNs are administered and distributed by five non-profit organizations called regional Internet registries (one for each continent).
- 4.
An edge is a link between two nodes (firms). A tie, as defined earlier, between two firms is represented by an edge between two nodes.
References
Ahrweiler P, Gilbert N, Pyka A (2011) Agency and structure. A social simulation of knowledge-intensive industries. Comput Math Organ Theor 17:59–76
Ahuja G (2000) Collaboration networks, structural holes, and innovation: a longitudinal study. Adm Sci Q 45(3):425–455
Antonelli C (ed) (2011) Handbook on the economic complexity of technological change. Edward Elgar, Cheltenham, UK
Antonelli C, Ferraris G (2011) Innovation as an emerging system property: an agent based simulation model. J Artif Soc Soc Simulat 14:1–63
Axelrod R (1997) The complexity of cooperation: agent-based models of competition and collaboration. Princeton University Press, Princeton, NJ
Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech Theor Exp 2008, P10008
Breschi S, Malerba F, Orsenigo L (2000) Technological regimes and Schumpeterian patterns of innovation. Econ J 110(463):388–410
Burt RS (2004) Structural holes and good ideas. Am J Sociol 110(2):349–399
Chesbrough HW (2003) Open innovation: the new imperative for creating and profiting from technology. Harvard Business School Press, Boston, MA
Chesbrough H, Vanhaverbeke W, West J (2006) Open innovation – researching a new paradigm. Oxford University Press, New York
Dahlander L, Gann DM (2010) How open is innovation? Res Pol 39:699–709
Edquist C (ed) (2003) The Internet and mobile telecommunications system of innovation. Elgar, Cheltenham, UK
Edquist C (2007) The internet and mobile telecommunications system of innovation. Edward Elgar Publishing, Cheltenham, UK
European Network and Information Security Agency (ENISA) (2011) InterX: resilience of the internet interconnection ecosystem. Report April 2011. Downloaded from http://www.enisa.europa.eu/activities/Resilience-and-CIIP/networks-and-services-resilience/inter-x/interx/inter-x
Fjeldstad Ø, Becerra M, Naravan S (2004) Strategic action in network industries: an empirical analysis of the European mobile phone industry. Scand J Manag 20(March–June):173–196
Fortunato S, Barthelemy M (2007) Resolution limit in community detection. Proc Natl Acad Sci U S A 104(1):36
Fraas M, Hauknes J, Smith K, Wibe M, Orstavik F (2001) Corporate governance and innovation in Nordic telecommunications. Report 9 – 2001. STEP Group, Oslo
Gilbert N (2008) Agent-based model. Quantitative applications in the social sciences, vol 153. Sage, Thousand Oaks, CA
Gilbert N, Pyka A, Ahrweiler P (2001) Innovation networks – a simulation approach. J Artif Soc Soc Simulat 4(3):8, downloaded from http://jasss.soc.surrey.ac.uk/4/3/8.html
Gilbert N, Ahrweiler P, Pyka A (2007) Learning in innovation networks: some simulation experiments. Phys A 378:100–109
Gilbert N, Ahrweiler P, Pyka A (2010) The SKIN (simulating knowledge dynamics in innovation networks) model. University of Surrey, University College Dublin and University of Hohenheim
Grandori A, Soda G (1995) Inter-firm networks: antecedents, mechanisms and forms. Organ Stud 16(2):183–214
Hagedoorn J, Schakenraad J (1994) The effect of strategic technology alliances on company performance. Strat Manag J 15:291–309
Hansen MT (1999) The Search-Transfer problem: the role of weak ties in sharing knowledge across organization subunits. Adm Sci Q 44:82–111
Hauknes J, Smith K (2002) Corporate governance and innovation in mobile telecommunications: how did the Nordic area become a world leader? Report R-12 – 2002. STEP Group, Oslo
Jansson J (2011) Emerging (Internet) industry and agglomeration: internet entrepreneurs coping with uncertainty. Entrepren Reg Dev 23(7–8):499–521
Lave J, March JG (1993) An introduction to models in the social sciences. University Press of America, San Francisco, CA
Lechler T, Taylor J, Klingenberg B (2007) The telecommunications carriers’ dilemma: innovation vs. network operation. In: Kocaoglu DF, Anderson T, Daim TU (eds) Conference proceedings PICMET 07: management of converging technologies, Portland, OR, vol 6, pp 2940–2947
Lozano S, Arenas A (2007) A model to test how diversity affects resilience in regional innovation networks. J Artif Soc Soc Simulat 10(4):8
Malerba F, Orsenigo L (1996) Schumpeterian patterns of innovation are technology-specific. Res Pol 25:451–478
March JG (1991) Exploration and exploitation in organizational learning. Organ Sci 2(1):71–87
McEvily B, Zaheer A (1999) Bridging ties: a source of firm heterogeneity in competitive capabilities. Strat Manag J 20(12):1133–1156
McGregor T, Alcock S, Karrenberg D (2010) The RIPE NCC Internet data measurement repository. Lect Notes Comput Sci 6032:111–120
Noteboom B (1999) Inter-firm alliances: analysis and design. Routledge, New York
Noteboom B (2002) Trust. forms, foundations, functions, failures and figures. Elgar, Cheltenham, UK
Ozman M (2007) Network formation and strategic firm behaviour to explore and exploit. J Artif Soc Soc Simulat 11(1):7, downloaded from http://jasss.soc.surrey.ac.uk/11/1/7.html
Powell WW, Koput KW, Smith-Doerr L (1996) Interorganizational collaboration and the locus of innovation: networks of learning in biotechnology. Adm Sci Q 41:116–145
Powell WW, White DG, Koput KW, Smith JO (2005) Network dynamics and field evolution: the growth of interorganizational collaboration in the life sciences. Am J Sociol 110(4):1132–1205
Pyka A, Gilbert N, Ahrweiler P (2007) Simulating knowledge-generation and distribution processes in innovation collaborations and networks. Cybern Syst 38(7):667–693
Rodan S, Galunic C (2004) More than network structure: how knowledge heterogeneity influences managerial performance and innovativeness. Strat Manag J 25(6):541–562
Schilling C, Phelps M (2007) Interfirm collaboration networks: the impact of large-scale network structure on firm innovation. Manag Sci 53(7):1113–1126
Sjölander S, Magnusson M, Andrén L (2001) Evolution, adaptation and entrepreneurial learning in the emerging Nordic wireless internet industry. Working paper 2001:5. Department of Innovation Engineering and Management, Chalmers University, Stockholm, Sweden
Taber CS, Timpone RJ (1996) Computational modeling. Quantitative applications in the social sciences, vol 113. Sage University Press, Thousand Oaks, CA
Teece DJ (1986) Profiting from technological innovation: implications for integration, collaboration, licensing and public policy. Res Pol 15(6):285–305
Teece D (1992) Competition, cooperation, and innovation: organizational arrangements for regimes of rapid technological progress. J Econ Behav Organ 18(1):1–25
Uzzi B (1997) Social structure and competition in interfirm networks: the paradox of embeddedness. Adm Sci Q 42:35–67
Zirulia L (2009) The dynamics of networks and the evolution of industries: a survey of the empirical literature, Ch. 3. In: Malerba F, Vonortas NS (eds) Innovation networks in industries. Edward Elgar, Cheltenham, UK, pp 45–77
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Blom, M., Hildrum, J.M. (2014). Firm-Level Business Strategies and the Evolution of Innovation Networks in the Nordic Internet Service Industry. 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_2
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