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Life cycle of technological Cluster
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Life cycle of technological Cluster

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Life cycle of technological Cluster Life cycle of technological Cluster Presentation Transcript

  • CLUSTERS FOR LIFE OR LIFE CYCLES OF CLUSTERSIn search for the critical factors of clusters resilience Raphaël Suire CREM-CNRS University of Rennes 1 Jérôme Vicente LEREPS University of Toulouse 1 Capitole & Toulouse Business School
  • BASIC QUESTION / SUMMARY• The question – The driving forces of clusters life cycles and resilience in turbulent economic environments (financial crisis, new growing societal paradigms, short life cycle in high-tech sectors)• Definition – According to the ecological metaphor (Holling, 1973), resilient clusters decrease their vulnerability through their endogenous adaptive ability to resist to exogenous shocks and stresses, by reorganizing themselves towards new technological fields and markets• Previous related works – From critical factors of clusters stability (Suire, Vicente, Regional Studies 2007, Journal of Economic Geography 2009) to critical factors of their resilience (this paper)• Results – Resilient clusters have to mix audience and networks effects along the phases of the composite technological process, and display core/periphery (degree distribution) and dissortative (degree correlation) structural properties
  • THE RESILIENT SILICON VALLEY 1 HP 21 Silicon Valley 150 Apple 41 ranking (sales) Intel 61 AMD Blue: computers 81 LSI black: semiconductors Google 101 red: Internet services Yahoo 121 Green: solartech E-bay 141 SunPower from MercuryNews 1611980s  1811990s   Hypothesis: The overlapping of knowledge and business domains in the Valley arise more from knowledge compositeness and transversality than from a simple and2000s  fortuitous co-existence
  • THEORETICAL BACKGROUND Location decision externalities • Audience and network effects • Marshallian vs. Jacobian externalities Stability of Clusters life Co-location locational cycles and process and norms and resilience technological technological critical factors relatedness standards Composite technologies life cycle Technological Structural properties of knowledge • Phases of the knowledge value overlapping and networks chain structural • Core/periphery • Standards diffusion and competition conditions for • Assortativity resilience• The related mechanisms of clusters resilience – Location decision externalities (Arthur, 1990; Appold, 2005; Romanelli, Khessina, 2005; Suire, Vicente, 2007-09) – Composite technologies lifecycle (Klepper, 1996; Malerba, Orsenigo, 1996; Audretsch et al, 2008) – Topologies of knowledge networks (Coleman, 1988; Burt, 1992; Jackson, Wolinsky, 1996; Barabasi, Albert, 1999; Newman, 2003)
  • 3 PROPOSITIONS• Proposition 1: Clusters life cycles depend, ceteris paribus, on the nature of location decisions externalities that govern the co-location process.• Proposition 2: The endogenous resilience capabilities of clusters are, ceteris paribus, a function of the particular overlap and feedbacks between the knowledge phases along the composite product life cycle.• Proposition 3: The resilient properties of clusters are, ceteris paribus, a function of their core/periphery structure and their degree of assortativity (degree distribution, degree correlation)
  • PROPOSITION 1• Location decisions of predecessors influence decision of followers, but according to different motives or different constraints (Suire, Vicente, 2009): – Legitimacy, reputation and cascade effects (audience effects) – Knowledge accessibility effects (network effects)• Geographical charisma and places reputation lead to unrelated knowledge variety (R&D productivity signal), as well as cognitive homophily (sectoral productivity signal), whereas micro-motives based on external knowledge accessibility can lead to related variety. Results in literature: network effects engender more stability for the aggregate structure than audience ones
  • PROPOSITION 2 • From idea to the market, knowledge processes are going through successive exploration and exploitation phases. Between both, for composite technological products, an integration phase occurs Ө2 • Demand characteristics evolve along the lifecycle: from ongoing development and non- zero default to well designed and price Ө1 competitive products or services. Ө0 • Innovations cross the chasm and diffuse from an early market (Ө1), to a mass market (Ө2), whenExploration Integration Exploitation the integration phase leads to a better satisfaction of consumers and an increase of demand. • Considering the battle of technological standards, successful clusters are the ones that succeed in crossing this chasm.
  • PROPOSITION 3• Sociology : Coleman, Burt and Granovetter: information and signals diffuse through social ties. Social capital, a resource that you get from social network, is a source of individual performance : trade-off between cohesion with natural homophilic behaviour and openness (weak ties), fresh air and non redundant signals• Economics : (Jackson & Wolinsky, 1996), if investment in a network is time, money or learning costly, then a rational individual should compare benefit and cost for each tie.• Complex systems : (Albert, Barabasi, 2002; Newman, 2003): Networks are not random structures and exhibit regular collective properties. Among them: – Scale free networks: preferential attachment and growth : the rich gets richer with power law distribution of degree  The hierarchy or the distribution of influences within the network and cohesiveness – The assortativity and openess  the network is assortative (positive degree correlation): the higher degrees interact with high degrees: the lowest degrees interact with low degrees  the network is dissortative (negative degree correlation): the higher degrees are tied with low degrees, the lowest degrees interact with high degrees
  • PROPOSITION 3– A random network, flat distribution of degrees, neither assortative nor dissortative: difficult to reach the critical mass for technological standardization– A core-periphery network with assortativity : easy to reach standardization but what next ? Lock-in and high sensitivity to external shocks– A core-periphery network with dissortativity : easy to reach standardization but what next ? Lock-out thanks to lower sensitivity to external shocks  resilient network
  • 4 evolutionarypathways ofclusters along themarket phases
  • THE DECLINING CLUSTER Ө0 Ө1 Beta test Early It does not succeed in crossing market market the chasm and stays locked into External audience and the Ө1 market due to: reputation effects prevailand knowledge homophily • Irrational exhuberance around a place or a technology : locational cascade and mimetic behaviours Declining clusters • Strong cognitive homophily with an excess of competition and a lack of coordination • Strong knowledge diversity which prevents from coordination External audience effects prevail and knowledge between heterogeneous heterophily profiles, which remain in isolated strategy • Rather flat hierarchy
  • THE DOMINATED CLUSTER Ө0 Ө1 Ө2 Beta test Early Chasm Mass market market market• Thanks to the network effects along the phases of technology development• Endogenous development with sectoral and complementary spin-offs as well as external actor locations. Connection between these peripheral members and the core of initial innovators: cohesive structure as a necessity to cross the chasm for a well-oriented exploitation• Deficient inter-cluster actors and geographical gatekeepers in charge of world-wide coordination: behind the battle of standard, the dominated cluster losts the battle of cluster• A hierarchy occurs with assortativity but not enough to exhibits the existence of global pipelines between major local hubs
  • THE DOMINANT CLUSTER Ө0 Ө1 Ө2 Beta test Early Chasm Mass market market market• Quiet similar to the previous one regarding the evolutionary path (strong cohesiveness) along Ө1 and Ө2 market except that gatekeeping strategies are observed. Strategic alliances in world-wide markets permit a global coordination on a very cost-oriented market strategy• The life cycle of the cluster follows the life cycle of the technology but it can decline with the demand decrease as soon as an assortativity of the network and a lack of knowledge variety prevent from investment in new emerging technological fields and markets• Strong hierachy within the cluster with a limited peripheral connected variety
  • THE RESILIENT CLUSTER Ө0 Ө1 Ө2 Beta test Early Chasm Mass market market market• Quiet similar to the previous one except that now the cluster exhibits dissortative property such that explorative behaviour and disruptive ideas are connected to the core of the network : knowledge heterophily• Necessity to have geographical gatekeepers (global diffusion) as well as in-betweenn actors, the linkers between periphery and core, such that overlapping practices and relational continnum co-exist.• This cluster exhibits resilience properties as its life cycle is disconnected from the technology life cycle• Cattani & Ferriani (2008) provide a convinced example of such a resilience for the Hollywood industry
  • CONCLUSION (1)• Clusters will be resilient if they combine network effects (the structuring of the technological field) and external audience effects (potential variety for markets overlapping)• Such a process is going through an evolving core/periphery structure – reinforcement of the standard in a cohesive structure – entrepreneurial connections with the periphery• For that, network cohesiveness, which is a regular result in the studies of collective behaviors, has to go with a certain level of dissortativity (as in physical networks), in order to engender more modularity and dynamical flexibility to the structure of knowledge flows• One of the reasons of the long and enduring success of the Silicon Valley is certainly due to the capacity of its social networks to play with mobility, dissortativity, cross-border knowledge, and beliefs on entrepreneurship
  • CONCLUSION (2)• Policy implications – Most of clusters policies, and European policies in particular, are based on the increase of the density of local knowledge interactions: “connecting people” one-best-way – A strict application of this basic principle can be under efficient (reinforcement of the core, negative lock-in and opportunistic behaviors regarding subsidies) – Need for more surgical and targeted interventions centered on particular missing links  Cluster failures arise more from a failure in the distribution of knowledge interactions rather than a strict weakness of their density per se – Need for diagnostic-based policies for more modular and dissortative networks, that connect in a more flexible way the core of well-established organizations to the myriad of burgeoning companies and science-based organizations, rather than the core in itself – Focusing on particular missing links rather than a general watering of public funds for coordination is suited to “repair” the lack of connectivity some clusters exhibit.