Industrial districts, innovation and I-district effect: territory or industrial specialization?



2.3. Industrial districts and innovation

Moulaert and Sekia (2003) differentiate six typologies of territorial
innovation models: industrial districts, their generalization as local
production systems,
milieux innovateurs, clusters of innovation, regional
innovation systems and learning regions. The literature on industrial districts
highlights the way that the district model fosters the innovative ability of
firms and helps promote a spiral process of generation and adoption of
innovations producing the I-district effect:

1. Innovation is the “genetic ability” of industrial districts (Piore and
Sable 1984; Bellandi 1996), a vital condition for confronting continuous and
discontinuous change. From an evolutionary point of view, industrial districts
are economic multicellular organisms embedded in a process of economic
selection. Districts change their traits through innovation in an attempt to
survive to the process of creative destruction.

2. Several types of mechanisms lead to new knowledge and
innovations (Bellandi 1992): R&D, learning-by-doing, learning-by-using,
entrepreneurship and the breaking up of the productive chain into many
phases. R&D is carried out by a few firms and technological institutes
although it does not constitute the main source of innovations
4. The main
amount of innovations seems to proceed from “spontaneous creativity”
(Becattini 1991) or “decentralized creativity” (Bellandi 1992), this is,
practical knowledge generated in learning-by-doing and learning-by-using
mechanisms and involving a large number of actors who need to be in touch
due to their necessity of continuous exchange. Another factor are spin-off
mechanisms of entrepreneurship, where new ideas or conceptions of the
production process lead to the creation of new firms or vice versa. Finally,
due to the competitive atmosphere the breaking up of the productive chain
into phases is more dynamic than in other environments and this fact fosters
innovation.

3. Short physical, social and cognitive proximities between the
district’s agents make fast and efficient processes of diffusion and absorption
of innovations possible. Alliances and direct cooperation between firms are
not the usual ways of diffusing innovations. This takes place through
(Becattini 1991; Bellandi 1992; Asheim 1994): (1) a social process where
there is informal exchange of information in public spaces or domestic life
between the workforce and, sometimes, the same entrepreneurs or managers;
(2) inter-firm mobility of workers; (3) the chain of specialized suppliers by

4 Bagella and Becchetti (2000) propose a theoretical model based on a game where
proximity reduces the appropriability of knowledge, positively affects the imitative
capacity of firms and fosters knowledge spillovers from firms with R&D expenditures
to other firms in the neighbourhood. As a result, the expenditure on R&D of
individual firms and aggregated R&D effort are lower in industrial districts although
other forms of technological innovation take on the same role.



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