tci 2015 characteristics and some cases of cluster evolutionary trajectories

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Characteristics and Some Cases of Cluster Evolutionary TrajectoriesChulwoo Lee, Professor, Dept. of Geography, Kyungpook Natl Univ., Korea

Jihye Jeon, PhD candidate, Dept. of Geography, Kyungpoon Natl Univ., Korea

Parallel Session 1.2: Analysis of Cluster Models and Cluster Ecosystems

Contents2. Research Background and Purpose. Adaptive Cycle Modeland Some Cases. Modified Cluster Adaptive Cycle Model1. Adaptive Cycle Model2. Cluster Adaptive Cycle Model1. Concepts2. Cluster Evolutionary Trajectories3. Significances and limits

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. Research Background and PurposeRecently, the development of ICT(Information and Communications Technology) and the high-tech industry, and then the globalization of economy and the shift of economic paradigm so called knowledge based economy Economic space including industrial districts is changing dynamically.Consequently, research on industrial districts so far...Static studies : analysis on formation factors and existence form(Park, 1994; Lee, 2011; Lee and Lee, 1998; 2000); development plan(Lee, 2004; Park, 2003); policy evaluation(Nam, 2004; Lee, 2005; Lee and Lee, 2007)Dynamic studies : discussion on evolution of industrial districts (interests in a series of historical evolution process such as emergence, growth, maturity and renewal of industrial districts especially in the field of institutional economic geography)

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4An appropriate perspective is to consider cluster as complex system, especially complex adaptive system(Martin and Sunley, 2011).Complex adaptive system is a suitable view for analyzing the evolution of cluster, so that it is characterized by the feedback between various components from micro to macro scale and changes to external shocks as well as self-reinforcing and self-organizing through internal co-evolutionary mechanismAmong the various models which can capture complex adaptive system, the most comprehensive model in terms of identity, stability, exogenous forcing is adaptive cycle model(Martin and Sunley, 2011).

. Research Background and Purpose

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5In Korea, some studies investigated the life cycle phases of industrial districts and the characteristics of each period by applying the life cycle model(Jeon, 2010; Koo, 2012; Jung, 2013). Under recognizing the limitations of life cycle model, some studies applied the adaptive cycle model to investigate cluster evolution, and suggested growth factors for future sustainable development(Huh, 2013; Nam, 2014).

. Research Background and PurposeIn this context, this presentation examines the various trajectories of industrial districts, their characteristics and some cases based on the adaptive cycle model.

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. Adaptive Cycle Model1. Adaptive Cycle Model

ConceptsClarifies the evolutionary process that super-system and sub-system affect each other, changing the structure and function of the entire system through complex feedback processes in ecosystems with circularity(Holling, 2001)Posits a four-phase process(exploitation, conservation, release, reorganization) of continual adjustment in ecological, social and environmental systems in terms of change of accumulation, connectedness, and resilienceAccumulation: the potential of accumulated resources available to the systemConnectedness: the internal connectedness of system componentsResilience: a measure of system vulnerability to and recovery from shocks, disturbances and stresses

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. Adaptive Cycle Model

Source: Holling, 2001; Martin and Sunley, 2011Period of experimentation and restructuring

Accumulation-low and variedConnectedness-lowResilience-increasesPeriod of stasis and increasing rigidity

Accumulation-slows and stabilizesConnectedness-lowResilience-increasesPeriod of growth and seizing of opportunities

Accumulation-rapid and focusedConnectedness-increasingResilience-highPeriod of contraction and decline

Accumulation-disinvestment and destructionConnectedness-lowResilience-increases(Re)emergence and growthStabilization, stagnation and decline< Adaptive cycle model of the evolution of a complex system >

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Martin and Sunley(2011) applied adaptive cycle model to clusters

. Adaptive Cycle ModelThroughout each step, capital accumulation, connectedness, resilience indicate the cycles.Three scenarios following the Release and Decline phase are shown: A, cluster disappears; B, the cluster undergoes a phase of renewal; and C, a new cluster emerges and replaces the old oneCapital accumulation: the accumulation of productive, knowledge and institutional capital; Connectedness: the extent of traded and untraded interdependencies among cluster firms; Resilience: the capacity of firms to respond flexibly to shocks internal or external to a cluster

< Stylized evolution of a cluster over an adaptive cycle >Source: Martin and Sunley, 20112. Cluster Adaptive Cycle Model

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. Adaptive Cycle Model3. Significance and limits

SignificanceThe model relies on an ecosystem analogy, and also allows for the possibility of system (cluster) renewal (recovery) as well as replacement, or maladaptive collapse at the same time. This seems to be valuable idea to explore cluster evolution.

The assumption that the evolution of a complex system always occurs through a four-phase sequence is restrictive Might be open to similar criticisms with the life cycle model

LimitsAn emphasis is not balanced between endogenous and exogenous forcing mechanisms to move a system though these four phase emphasis on endogenous mechanismsA rather restrictive allowance for the two-way nature of the interaction between a cluster and its external environment

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. Modified Cluster Adaptive Cycle Model

Martin and Sunley(2011) recognized numerous development trajectories according to complex interactions between clusters and their environment, and contingent and strategic decision-making by cluster-based firms.They modified and expanded the adaptive cycle model, and then suggested six different possible sequential trajectories.Cluster full adaptive cycle, Constant cluster mutation, Cluster stabilization, Cluster reorientation, Cluster failure, Cluster disappearance

< Modified cluster adaptive cycle model >Source: Martin and Sunley, 20111. Concepts

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112. Cluster Evolutionary Trajectories


1) Cluster full adaptive cycle (rK)Phases and CharacteristicsEmergence, growth, maturation, decline and replacement by a new cluster.The replacement cluster would draw upon resources and capabilities inherited from the old clusterThe cluster atrophies due to internal rigidities or exhaustion of increasing returns effectsBut a new cluster emerges by utilizing the inherited resources and capabilities

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1) Cluster full adaptive cycle (rK)Example

The growth of polymers after the decline of the tyre cluster, Akron, Ohio (Carlsson, 2001)The growth of low-carbon technology industries, the Ruhr, GermanyThe basis of a creative district focused on specialist retailing after the shrinkage of the Birmingham jewellery quarter, UK (De Propris and Lazaretti, 2008)An outdoor equipment and clothing industry after the decline of textile and steel industries (Parsons and Rose, 2005)The Seoul Digital Industrial Complex, Seoul, Korea (Koo, 2012)

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2) Constant cluster mutation (rrr)Phases and CharacteristicsEmergence, and growth with constant structural and technological changeThe cluster continually adapts and evolves, by the successive development of new branches of related activity. The basic technology would have a comprehensive characteristicsCluster firms are able to innovate continuously and the cluster constantly mutates or widens in terms of industrial specialization and technologyThere are high rates of spin-offs and spin-outs from local firms, research institutes, or universities

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2) Constant cluster mutation (rrr)

ExampleOpen network clusters, such as Silicon Valley and Medicon Valley (Moodysson et al., 2008)The Cambridge high-technology cluster, UK (Garnsey and Heffernan, 2005; Stam and Garnsey, 2009)The Dague Seongseo Industrial Complex, Daegu, Korea (Lee, 2007; Lee, 2008)

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3) Cluster stabilization (rKK)Phases and CharacteristicsEmergence, growth, maturation, and stabilizationThe cluster might remain in a much reduced and restricted form for an extended period of timeThe remaining firms in the cluster would survive by upgrading products and/or focusing on niche or prestige market segmentsThough the cluster retains a modest degree of resilience, it remains potentially vulnerable to (further) decline

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3) Cluster stabilization (rKK)

ExampleLock-manufacturing cluster, the West Midlands (Bryson et al., 2008)Transition from the production of final goods to the production of machinery in some Italian districts (Rabellotti et al., 2009)Diversification into export markets in Aberdeen oil complex (Chapman et al., 2004)Machine Industrial cluster of Changwon, Korea (Lee, 2003)

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4) Cluster reorientation (rK)Phases and CharacteristicsEmergence, growth, onset of early cluster maturation or decline, and reorientationFirms re-orientate their industrial and technological specialisms upon reaching or nearing maturation or decline phase, and new cluster emerges The cluster branches into a new formThe more innovative leading firms may play a key role by reacting to market saturation or a rise of major competitorsA technological breakthrough may activate reorientation

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4) Cluster reorientation (rK)

ExampleRadical product diversification in the Montebelluna sportswear cluster (Sammarra and Belussi, 2006)The Boston high-technology cluster (Bathelt, 2001)The financial services cluster in the City of London (Martin and Sunley, 2011)The Gumi National Industrial Complex (Chung, 2011)

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5) Cluster failure (f)Phases and CharacteristicsEmergence and failure to take off and growAny remaining firms dont constitute a functioning clusterThe cluster fails to achieve sufficient critical mass, externalities or market share, the firms would create unstable innovationNew firm formation is low and/or the firm failure rate is high, which deters new entrants

ExampleA digital cluster in Dublin (Bayliss, 2007)

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6) Cluster disappearance (rKd)Phases and CharacteristicsEmergence, growth, maturation, decline and eliminationNo replacement by a new clusterThe inherited resources and competences are not sufficient or ill-suited to form the basis of new cluster formation

ExampleSheffield steel (Potter and Watts, 2010), Dundee Jute (MacKay et al., 2006), Como silk (Alberti, 2006)The Staffordshire pottery and ceramics district (Sacchetti and Tomlinson, 2009)Coal industry in Taebaek, the abandoned coal mine areas in Munkyung, Korea

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ReferencesCarlsson B., 2001, Institutions, entrepreneurship, and growth: biomedicine and polymers in Sweden and Ohio, Small Business Economics 19, 105121.Chung. D.C., 2011, Evolution of industrial cluster through overcoming the lock-in effect of branch plant agglomeration.De Propris L. and Lazaretti L., 2008, Measuring the decline of a Marshallian industrial district: the Birmingham jewellery quarter, Regional Studies 43, 11351154.Holling C.S., 2001, Understanding the complexity of economic, ecological, and social systems, Ecosystems, 4, pp.390-405.Huh, D.S., 2013, The evolution of the IT service industry in the U.S. national capital region: the case of Fairfax county, Journal of the Economic Geographical Society of Korea, 16(4), pp.567-584.Koo, Y.M., 2012, Analysis of cluster life cycle on the dynamic evolution of the Seoul digital industrial complex in Korea, Journal of The Korean Association of Regional Geographers, 18(3), pp.283-297.Lee. C.W., 2003, Exploring regional system of innovation in Changwon, , 23, pp.327-344.Lee. K.-M., 2007, The characteristic and evaluation of the governance of the vitalization policy of metropolitan industrial complex: the case study of Seongseo Industrial Complex in Daegu, MA.Martin R. and Sunley P., 2011, Conceptualizing cluster evolution: beyond the life cycle model?, Regional Studies, 45(10), pp.1299-1318.Moodysson J., Coenen L. and Asheim B., 2008, Explaining spatial patterns of innovation: analytical and synthetic modes of knowledge creation in the Medicon Valley life-science cluster, Environment and Planning A 40, 10401056.Nam, K.B., 2014, Path dependence and resilience process of the Seoul Digital Industrial District, Seoul, Korea, The Geographical Journal of Korea, 48(3), pp.375-388.

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tci 2015 characteristics and some cases of cluster evolutionary trajectories

Economy & Finance