Evolving networks of inventors

Abstract

In this paper a model for the formation of strategic alliances is studied. Innovation results from the recombination of knowledge held by the partners to the collaboration, and from the history of their collaboration. Innovation brings partners closer together, while at the same time the repetition of partnerships fosters trust and helps improving the outcome of each round of cooperation. A tension exists between innovating with people I know in order to reduce uncertainty at the expense of the net benefit from our joint effort, and innovating with strangers with whom the outcome of joint innovation can be greater but at a larger risk of failure. This "organized proximity", built through the experience of cooperation, can be at the origin of strongly structured networks of innovation, where agents' relations focus on limited cliques of partners. JEL Classification: L14, Z13, O3

The Spatio-Relational Nature of Urban Innovation Systems: Universities, Knowledge Intensive Business Service Firms, and Collaborative Networks

“…Secondly, it is argued that, on its own, geographic proximity is insufficient to create synergies and foster interaction between firms ( Typically, non-spatial proximity is conceptualised in terms of similarities between agents based on: shared knowledge bases or skills (cognitive proximity); shared methods and procedures (organisational proximity); shared relationships (social proximity); and shared culture (institutional proximity) (Aguilera et al 2012). Cowan et al (2006) model the innovation process as a search process in which firms face a trade off between developing collaborative linkages with a familiar partner or a partner with complementary knowledge. One important finding from this work is that as a firm's network becomes denser it does not grow in geographic scope, thus "reinforcing local coherence" (Cowan et al 2006).…”

“…Cowan et al (2006) model the innovation process as a search process in which firms face a trade off between developing collaborative linkages with a familiar partner or a partner with complementary knowledge. One important finding from this work is that as a firm's network becomes denser it does not grow in geographic scope, thus "reinforcing local coherence" (Cowan et al 2006). Therefore, within this model it is the notion of organisational proximity that drives the localisation of collaboration.…”

Evolutionary models in economics: a survey of methods and building blocks

“…One way to deal with this rather unrealistic setting is to limit the environment in which agents operate (Kirman 1997). This can be achieved by assuming that agents interact with a limited number of other agents, for instance, through networks (Axelrod 1997;Janssen and Jager 2002;Verspagen 2003, 2005a;Morone and Taylor 2004;Cowan and Jonard 2004;Cowan et al 2006). The latter predominates in evolutionary multi-agent models, which allow for explicit modelling of interactions within and between heterogeneous groups, and within networks of consumers (Section 2.3).…”

Challenges for scientometric indicators: data demining, knowledge-flow measurements and diversity issues

“…The latter are particularly concerned with designing incentives and costs associated with scientific production (Stephan 1996) and address the creation and persistence of social links (e.g. coauthorship, Jackson & Wolinsky 1996; network of inventors, Cowan et al 2006), sometimes in the formalism of game theory.…”