Urban Innovation and Collective Learning: Theory and Evidence from Five Metropolitan Cities in Europe

  • Roberta Capello
Part of the Advances in Spatial Science book series (ADVSPATIAL)


The tendency for innovation activity to cluster in large metropolitan areas is a widespread and well established phenomenon. Such areas are often regarded as ‘centres of creativity’ and have recently been referred to as ‘islands of innovation’, due to their capacity to induce economic progress and technological innovation (Davelaar and Nijkamp 1990; European Commission 1995; Hingel 1992; Simmie 1998 and forthcoming). The main explanation for their success is that they generate much greater agglomeration economies than elsewhere, so the metropolitan area is often conceived of as a breeding place for new activities. As has already been suggested (Glaeser et al. 1992), such a dynamic view of the city fits nicely with the recent approach to economic growth, which sees externalities [and particularly externalities associated with the stock of knowledge] as the ‘engine of growth’ (Romer 1986; Lucas 1988).


Small Firm Large Firm Innovation Activity Knowledge Spillover Innovative Activity 
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  1. 1.
    A vast literature exists on the social homogeneity of local districts. See among others, Bagnasco and Trigilia (1984); Becattini (1979, 1990). For an overall synthesis of local district theories see Rabellotti (1997); Bramanti and Maggioni (1997); Pietrobelli (1998).Google Scholar
  2. 2.
    The idea that territorial proximity is insufficient for milieu mechanisms has already been put forward by the French school on ‘proximity’. See, among others, Bellet, Colletis and Lung (1993); Dupuy and Gilly (1995); Rallet (1993); Gilly and Torre (2000).Google Scholar
  3. 3.
    Factor analysis is a statistical technique used to identify the factors that can be used to represent relationships among sets of interrelated variables. The basic assumption is that underlying dimensions, or factors, can be used to explain complex phenomena. The goal of factor analysis is thus to identify not-directly-observable factors through a set of observable variables, therefore reducing the number without losing too much of their explanatory power.Google Scholar
  4. 4.
    A similar result was found in relation to the innovative behaviour of firms in the metropolitan area of Milan (see Capello 2001, forthcoming).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Roberta Capello
    • 1
    • 2
  1. 1.Department of EconomicsUniversity of MoliseItalia
  2. 2.Department of Economics and ProductionPolitecnico MilanoItalia

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