Estelle Vallier - Innovation in Clusters

In the eastern United States, Route 128 is more composed of significant autarkical structures and the links between individuals are therefore characterized by a principle of corporate loyalty (Saxenian 2000). In the relationships between businesses, customers and suppliers, individuals refer first and foremost to the vertical hierarchy of the organization to which they belong, before circulating information horizontally between firms. For Saxenian, the performance of Silicon Valley, or its advantage, to use Porter’s terminology, depends on local social and institutional determinants, such as professional or commercial organizations, far more than economic and fiscal factors (wage differentials, real estate costs, local taxes). For example, The Semiconductor Equipment and Materials International or The Software Entrepreneur’s Forum organize meetings, dinners, seminars and training courses and participate in the creation of these social networks (Grossetti 2004, p. 170). From this point on, we can observe how interactions embedded in a given framework (in this case the businesses in the Valley) can be decoupled in another context (professional association, for example).

In another study of Silicon Valley, Michel Ferrary particularly observes the social networks of the French community living and working in the Valley. These French expatriates meet in “non-economic social institutions” (the French school in Palo Alto, the Maison Française, the film club, French restaurants), ethnic celebrations (the July 14 national holiday, the Beaujolais Nouveau day), newspapers and associations with a more economic purpose (Doing Business in French, Eurotrash, Silicon French). They develop strong ties of friendship, support and appreciation through cultural and social activities during which they meet (Dibiaggio and Ferrary 2003). According to Ferrary, they mobilize this community in the economic activities in which they are engaged. We can therefore see that literature highlights the virtuous development of these territorial concentrations by emphasizing the effects of geographical proximity in the constitution of social networks.

Since the beginning of the 1990s, the economics of proximity (Bellet et al . 1993, 1998; Rallet and Torre 1995; Gilly and Torre 2000; Dupuy and Burmeister 2003; Pecqueur and Zimmermann 2004; Torre and Filippi 2005) has sought to take account of the conditions necessary for the coordination of agents (Talbot and Kirat 2005, p. 9). This question has been the subject of research concerning the links, or otherwise, between geographical proximity and social interactions. The abundant work has led to “the emergence of a kind of specific scientific community, with its own conferences and regular publications” (Bouba-Olga and Grossetti 2010, p. 2). In the course of their work, this school has managed to define a certain number of types of proximity, but a concern for readability has led its authors to restrict the canonical forms of proximity to two ( ibid ., p. 4). Thus, they agree to say that alongside geographical proximity is organized proximity. The former is doubly relative: on the one hand, it is relative to the means of transport and, on the other hand, it proceeds from the judgment of the individuals on the distance that separates them from other individuals or groups. The latter is not geographical, but relational in nature and is based on an organization’s ability to have its members interact (Talbot and Kirat 2005). Beyond this vertical distinction, the authors have made a horizontal division within organized proximity between the logic of belonging (to the same structure, for example) and the logic of similarity (sharing common representations and a common system of values). The authors stress that the two proximities can be combined and thus facilitate knowledge sharing. Nevertheless, geographical proximity does not guarantee organized proximity, the absence of which translates into an extreme weakness of cooperative relations, solidarity links or shared representations (Torre and Zuindeau 2012, p. 354). Moreover, some authors postulate that spatial proximity may lead to negative externalities of agglomeration, such as industrial espionage, unbridled competition, local market saturation or the poaching of qualified personnel (Depret and Hamdouch 2009, p. 32).

Given the limits of geographical proximity (negative externality, absence of spontaneous links, etc.), other relational logics between scientific and industrial actors have been studied. Estades, Joly and Mangematin propose three relational logics (Estades et al . 1996): proximity, club and market. These three logics were later completed by Grossetti and Bès (2001), who then distinguished a “network logic” in which the contact results from a relational chain linking the two officials responsible for the collaboration. Most often, this relational chain has its roots in the university courses studied by the two officials. This network logic partially challenges the logic of proximity established by Estades, Joly and Mangematin, insofar as, for Grossetti and Bès, personal networks do not only stem from local proximity. They also identify “institutional logic”, which is almost similar to the “club logic” of Estades, Joly and Mangematin, since both refer to the intervention of an external body, most of the time governmental, which provokes interactions between enterprises and laboratories. Finally, the two studies establish a third similar logic: that of the market. Estades, Joly and Mangematin consider that partnerships of this type are often the result of the will of industrialists who need solutions provided by researchers, whereas Grossetti and Bès consider that both scientific and economic actors can lead this market logic (Grossetti and Bès 2003, p. 343).

Ten years after the Grossetti and Bès study, Julien Barrier also identifies three major patterns of academic and industrial interaction (Barrier 2014). For him, the relationship is most often created on the initiative of industrialists who seek to: (1) enter into collaboration with researchers in order to acquire specific knowledge and know-how in a well-defined field, (2) optimize an existing technology that enables researchers to test theoretical models in an industrial context or (3) jointly explore, upstream of the development or application phase, concepts or research objects that are beneficial to the scientific production of academic researchers (Barrier 2014, p. 63). Geographical proximity is therefore gradually being supplemented by analyses that focus on other types of proximity and relational logic. Alongside these proximities, the sharing of a common social capital, which is decisive for establishing links, has also been the subject of several works.

A number of works emphasize the role of individuals’ social capital in facilitating the development of economic activities (Bourdieu 1980; Coleman 1994; Burt 1992). Coleman was particularly interested in the relationships and knowledge of individuals. In this approach, the social network becomes a resource in the same way as cultural or economic capital. In his works on Rational Choice Theory, he defends the idea that the individual determines his choices, not only on the basis of the economic calculation in terms of cost/benefit ratio but also on the basis of his relationships and knowledge. These authors do not question the idea that individual behavior is determined by economic incentives and financial resources. They add that they are also determined by motivations and social resources such as reputation, legitimacy and address books (Lanciano-Morandat et al . 2009, p. 180). This position is in line with the Bourdieusian thesis that capital must be accumulated in order to be fully operational. Another resource is then regularly evoked in the study of these social exchanges: trust. Social capital is not enough, and some authors argue that the condition for economic progress is the development of trust between people, understood to be the expectations nurtured by one individual towards the explicit or implicit promises of another (Dasgupta 2011, p. 50). Thus, in line with this work, some have analyzed the social capital of entrepreneurs as a decisive resource in the realization of a cluster (Feldman 2001; Feldman et al . 2005), considering that a network analysis of firms is, in fact, a network analysis of individuals: