Guichard (2004a) recalls the interest of sociological approaches that understand the encounter between different social worlds in terms of processes. Her analysis relies particularly on “technoeconomic networks”. These are defined as “a set of heterogeneous actors – public laboratories, technical research centers, industrial firms, financial organizations, users, and public authorities – which participate collectively in the development and the diffusion of innovation and which via numerous interactions organize the relationships between scientifico-technical research and the marketplace” (Callon 1991, p. 220). Guichard points out the role of an actor who “shifts and transforms ideas, means, objects, roles and their links and maintains various interests in alignment until a single solution emerges” (Guichard and Heisbourg 2004, p. 97). According to this solution, Guichard refers to this role as that of “translator” within “dual networks”.
According to this approach, network construction is a collective challenge centered on this translator. She recalls that these networks have variable geometry and go beyond the set of actors composing them, and are also composed of a set of intermediaries such as written documents (scientific articles, reports, patents, etc.), embedded competences (mobile researchers, engineers moving from one company to another, etc.), money (cooperation agreements between a research center and a company, financial loans, a client purchasing a good or a service, etc.) and more or less elaborated technical objects (prototypes, machines, end-user products, etc.). They are structured around three poles, each of which has its role: the scientific pole (knowledge production), the technical pole (design of a coherent object able to provide services) and the market pole (groups the users and defines the demand). Therefore, the dual network is a specific case of a technico-economic network (TEN). According to this approach, technology is not a priori defined as dual. Its development at the core of a network grouping two different social worlds, the defense and civilian worlds, through the interactions it generates, confers technology a dual nature.
Assuming that the duality of a technology is defined by the network in which it is developed, this analysis of duality comes close to the framework of analysis developed by Kulve and Smit (2003). They reworked the TEN and proposed the concept of STN, which they apply to the specific case of duality. They developed the idea that the social network within which technologies are developed determines the dual nature of a technology, unlike other approaches that focus on uses or financing, for example. It is a network of dual actors working together around the same technology that makes it possible to qualify the respective technology as “dual” (Guichard 2004a, 2004b; Guichard and Heisbourg 2004). Within this theoretical framework, the way to understand duality resumes the principles established by Cowan and Foray (1995, 1997), which stipulate that the transfer of a technology developed in an innovation network entirely dedicated to defense toward the civilian sector (or vice versa) is rather a proof of the absence of duality.
Duality no longer involves the organization of transfers, but the use of possible synergies between civilian and defense sectors during the innovation process. It is perceived as a window of opportunities. Such a network is a set of social interactions, whose stability generates high resilience. Therefore, the nature of these relations is essential for maintaining success; this relies particularly on the involvement of actors dedicated to the construction of the dual network, whose role is particularly pointed out. Furthermore, Kulve and Smit mention the set of other factors leading to the success or failure of such a network (Table 1.2). They point out the policies aiming to develop certain competences associated with the construction of such networks as key factor of the successful integration of civilian and military industrial and technological bases (Kulve and Smit 2003).
Table 1.2. Success or failure factors of duality (source: Guichard and Heisbourg 2004, p. 102)
| Success factors | Failure factors |
|---|---|
| Actors dedicated to network construction | No dual financing possibility |
| Mixed network of civilian, military and dual actors | No common “dual” purpose of the participants |
| Significant technological overlapping of various applications | Differences between lifecycles of the applications |
Moreover, many authors underline the fact that the elaboration of complex systems (also referred to as CoPS) involves mastering wider knowledge. Such knowledge is rarely concentrated within a single actor, consequently mechanisms for knowledge management throughout networks are required. New possibilities of interactions between actors emerged in order to create fully or partially dual technologies. In this context, the protection of innovations and their valorization are essential. New practices are established in the defense industry and they modify the organization of companies given the fact that the management of intellectual property rights (IPR) requires new competences (Ayerbe et al. 2012, 2014).
Innovation networks are particularly dense (Cantner and Pyka 2001; Kuhlmann 2001). Duality led to the emergence of new actors within the innovation networks of the defense world. The complexity of knowledge management increased (Mérindol 2004). In the 1990s, the emergence of “systems of systems” (systems interconnected through information and communication systems) facilitated technology transfers between defense and civilian sectors. This was done jointly with the emergence of LSI, characterized by the role of evaluator, manager and architect of programs that certain companies had to assume (Lazaric et al. 2011). Consequently, LSI is a key actor of dual innovation network, as it is the one that, mastering the system architecture, is able to integrate knowledge coming from both civilian and military sector. Besides mastering the system-related knowledge architecture, integrating such a system requires knowledge associated with subsystems or other components (Prencipe 1997; Hobday et al. 2005).
In the case of a dual innovation network, LSI draws its knowledge from both civilian and defense worlds (which makes it a bridge between these two worlds) and develops organizational competences that cannot be dissociated from this activity in order to achieve it. Therefore, it plays a role in what some refer to as “coopetition” between the actors of a network (Depeyre and Dumez 2010).
Nevertheless, the consideration of duality through a network is not always satisfactory, as it focuses on coordination between actors. If systemic approaches are used, the analysis can include structural and institutional components, whose evolution can be assessed. This type of analysis relates to both defense and civilian sectors and stresses the governance problems in the implementation of duality.
1.3.2. Dual policies of innovation
Understanding duality from the systemic perspective amounts to studying the institutional, organizational, legal and financial arrangements. The problems raised vary in nature and often highlight the intangible aspect of the notion (knowledge, competences, informational proximities, etc.). This also points out the system governance problems and, consequently, the public policies associated with this form of coordination between civilian and military sectors. This is how the concept of “dual policy” or “duality policy” emerges. “It corresponds to the search for an organization of knowledge and information exchange in which the State is the facilitator. Public authorities must define the common research themes and initiate knowledge and information exchanges between the civilian and military research sectors” (Mérindol 2004, p. 102).
Although duality is not at the core of their analysis, Uzunidis and Bailly (2005) deal with the relation