In this paper we argue that the nature of networks as intangible assets is connected to their economic efficiency in producing innovation. We do so by reviewing a stream of literature from two different perspectives. Firstly we look at the empirical research on innovation, with its recurrent theme of vertical disintegration. Secondly we turn to the theory of vertical integration itself, which requires innovation to justify idiosyncratic demand shocks that apparently explain the existence of network industrial structures. We suggest that a recently developed model of bipartite networks, proposed by Kranton and Minehart (2000), may be a useful way of looking at innovation in industries where new technologies and products are normally supplied by third-party suppliers rather than in-house. The model's predictive power, however, is undermined by an excess of equilibria and, perhaps, a lack of realism (innovation for example is always achieved by investing a fixed amount in R&D). Moreover, most of the equilibrium networks in the model turn out to be inefficient.
Dynamic networks in innovation intensive industries / Cottica, A.; Ponti, Giovanni Benedetto. - (2004), pp. 137-152.
Dynamic networks in innovation intensive industries
PONTI, GIOVANNI
2004
Abstract
In this paper we argue that the nature of networks as intangible assets is connected to their economic efficiency in producing innovation. We do so by reviewing a stream of literature from two different perspectives. Firstly we look at the empirical research on innovation, with its recurrent theme of vertical disintegration. Secondly we turn to the theory of vertical integration itself, which requires innovation to justify idiosyncratic demand shocks that apparently explain the existence of network industrial structures. We suggest that a recently developed model of bipartite networks, proposed by Kranton and Minehart (2000), may be a useful way of looking at innovation in industries where new technologies and products are normally supplied by third-party suppliers rather than in-house. The model's predictive power, however, is undermined by an excess of equilibria and, perhaps, a lack of realism (innovation for example is always achieved by investing a fixed amount in R&D). Moreover, most of the equilibrium networks in the model turn out to be inefficient.File | Dimensione | Formato | |
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