Economic Geography - Clusters: knowledge and proximity

Introduction

  • Understanding firms' location is a key research area in economic geography.
  • Since the late 1800s, there's been recurring interest in industries agglomerating and clustering.
  • This interest renewed in the 1980s due to new economic growth geographies under post-Fordism.
  • There's a paradox of "sticky places" (clusters) versus "slippery spaces" (ICTs, TNCs, globalisation).
  • New approaches focus on understanding the geography of access to specialist knowledge via proximity and clustering.
  • Clustering is increasingly significant for the competitiveness of nations, regions, and cities.

Aims

  • Understand why proximity matters for economic activities.
  • Explain the economic and socio-institutional forces binding actors in clusters.
  • Appreciate critiques of localised perspectives on proximity.

Outline

  • Introduction and conceptual underpinnings
  • Clusters and their limits
  • The importance of proximity with case studies.
  • Summary and conclusions.

Agglomeration Economies: ‘Traded Interdependencies (1)’

  • Weber (1929): Industrial location theory with agglomeration as a deviational force.
  • Alfred Marshall (19th century): Agglomerations like the Sheffield steel industry and its “industrial atmosphere”.
  • Cost advantages of ‘external economies’ (relations external to the firm):
    • Intermediate industries: Supplier linkages
    • Labor pool
    • Hard and soft infrastructures
  • Localisation economies
  • Urban economies

Post-Fordism: Re-emergence of Agglomeration and Proximity

Agglomeration Economies: ‘Traded Interdependencies (2)’

  • 1980s/1990s: New geographies of economic growth.
  • Regional growth as part of Post-Fordist shift & globalisation:
    • New Industrial Districts (e.g. Third Italy)
    • High Technology Sunbelt areas (e.g. Silicon Valley)
  • Allen Scott (1988): ‘New Industrial Spaces’
  • Vertical disintegration and externalisation of production.
  • Transaction costs thesis based on material linkages, cost benefits, and flexibility of proximity.
  • Led to emergence of institutionalist perspectives (e.g. Amin 2000).

Agglomeration Economies: ‘Untraded Interdependencies (3)’

  • Learning and innovation are also derived from proximity.
  • Specialist (e.g. tacit) knowledge exchanged and developed in particular places:
    • Informal linkages between firms, workers in a particular place
    • Collaborative projects; routine communications between firms etc.
    • Labor market (people moving jobs)
    • Social & professional organisations; universities etc.
  • Creates ‘local worlds of production’.
  • Inspired concepts like ‘learning regions’.

Clusters and their limits

‘Bringing it together’, knowledge, proximity and competitiveness: the Cluster concept

  • Cluster concept: Michael Porter (1998) defines clusters as “geographical concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries, and associated institutions (e.g. universities, trade assocs) that compete but also collaborate”.
  • Firms must be linked in some way (e.g. supply chains).
  • Geographically concentrated: proximity creates commonality of interest and interaction.
  • Learning spill-overs occur.
  • Geographical clustering of industries is key to national competitiveness.

Porter’s Diamond Model of the cluster concept

  • Factors:
    • Land, capital, labor, and knowledge
  • Demand Conditions:
    • Close links between customers and suppliers; learning and knowledge transfer; critical mass
    • Leading edge local customers who serve global markets; stimulates innovation
  • Related and supporting industries:
    • Range and depth of firms, new firm formation; rivalry and collaboration

Case study: Motorsport Valley Cluster

  • 75% of single-seat racing cars emanate from MSV.
  • 7 of 11 F1 teams are based in the UK.
  • Over 40,000 employees.
  • £6b business (Source: Coe et al 2020).

The role of knowledge and untraded interdependencies in the MSV cluster

  • Staff turnover
  • Shared suppliers
  • Firm births and deaths leading to mixing and diffusion of knowledge
  • Informal collaborations on things like regulations
  • Industry gossip
  • Trackside observations: testing and racing
  • Unique ‘place based’ phenomena?

Career histories, spin-offs, working relations etc: 'knowledge exchange processes'

The limits to clusters and proximity?

  • Variability: Coe et al (2020) develop an 8-fold typology ranging from high-tech innovative clusters to labor-intensive craft production clusters
    • Design-intensive craft production (e.g. Third Italy)
    • Flexible production hub and spoke clusters (e.g. Toyota city)
    • Production satellite clusters (e.g. call centres/BPO; e.g. Manilla)
    • Labour intensive craft production (e.g. garment district on NYC)
    • Hi-tech innovative clusters (e.g. Cambridge; Boston USA)
    • Business Service clusters (e.g. London)
    • State-anchored clusters (e.g. Singapore’s Biopolis)
    • Consumption clusters (e.g. Las Vegas)
  • Capitalist imperative ‘v’ high-road knowledge-led approach
  • Varying scales: local to national (e.g. Singapore)
  • How clusters evolve (differently)?
  • Over prioritising the ‘local’?:
    • Underplay the role of broader spatial divisions of labour, inter-regional relations, power etc.
    • The role extra-local sources of knowledge

Local and global learning and knowledge?

  • Local agglomerations ‘buzz’ needs to be plugged into global pipelines?

The importance of proximity? Case studies in action

  • Wide array of case studies to explore:
    • UK
    • EU
    • US
  • Much of the recent attention has focused on ‘tech-sector’ and ‘start-ups’

Silicon Roundabout – Shoreditch London

  • Agglomeration of tech start-up firms in the Old Street area of London

Silicon Roundabout – Shoreditch London

  • Explore the roles of clustering, knowledge and proximity in its formation and evolution (Foord 2013)
  • What role for knowledge & proximity versus other locational factors?: costs; lifestyles etc?
  • Consider the potential impact of the Government’s support, from Tech City to Tech Nation:
    • What value-added has policy provided? Branding, firm growth, productivity etc?
    • Making things bigger, not better?
  • Multi-scalar nature of the cluster dynamic and the shifting geographies of the sector. London as the ‘technology ecosystem’ – buzz and pipelines?

Connections to Geo2124 Berlin……..

Conclusion

  • Enduring role of agglomeration processes
  • Post-Fordist production renewed the propensity for agglomeration and clustering
  • Clusters: derived from benefits of agglomeration, through traded and non-traded interdependencies
  • Exchange of knowledge via proximity increasingly seen as a driver of clustering and their competitiveness
  • Limits of clusters as a concepts:
    • Variation
    • Local and non-local
    • Other forms of proximity and knowledge exchange