to the approach proposed by Guichard (2004a, 2004b). The challenge is then to classify technologies in order to evaluate duality. If uses are no longer considered key factors for duality, then it is possible to reduce the bias of the analysis linked to fluctuations in the acquisition policies of Defense Ministries. Moreover, while uses are essential in assessing the criticality of a technology for defense operations, they provide no explanation for a potential technological transversality. How a technology is used gives no indication on its technological characteristics. In this case, an essential distinction lies at the basis of this analysis. The dual use of a technology (market-related duality) should be distinguished from dual innovation (production-related duality).
A second theme approached in addition to duality, and deriving from it, is that of technological innovation as such. When studying innovation, the definition proposed by the second edition of the Oslo Manual can be used, namely: “Technological product and process innovations (TPP) comprise implemented technologically new products and processes and significant technological improvements in products and processes. A TPP innovation has been implemented if it has been introduced on the market (product innovation) or used within a production process (process innovation)” (OECD 2005). By this definition, it is the very essence of innovation to provide companies with a competitive edge. This definition resumes the position supported by Porter (1985), who presents it as key to company competitiveness. Companies willing to maintain sustainable competiveness on a constantly evolving market must have innovation at the core of their strategies.
Moreover, companies are at the center of the innovation process: seizing technological opportunities is a first step that must be followed by protecting the advantage thus obtained, which is key to capitalizing on it (Teece 1986). A company can implement several protection regimes, with various performance levels in terms of degrees of appropriability (Dosi 1988). Six appropriation instruments are commonly identified (Levin et al. 1985): patents, secrecy, lead time, effects of the learning curve, duplication cost and time and the efforts involved in sales and high-quality services. While patents are acknowledged as an efficient product innovation appropriation mechanism, secrecy, lead time and the effects of the learning curve are considered as efficient for process innovation protection. The latter are nevertheless difficult, if not impossible, to understand, at least as far as secrecy, a very significant concept in defense industry, is concerned.
Technology draws particular attention from economists, who, among others, attempt to formulate a precise definition of this term. There are many approaches according to which technology – sometimes referred to as “technique” – is not considered as a simple artifact. It is obviously composed of one or several artifacts, but it may also include technical systems, knowledge, a social environment or uses (Pinch and Bijker 1984; MacKenzie 1993; MacKenzie and Wajcman 1999; Bijker 2010; Bijker et al. 2012).
Knowledge plays an essential role in these approaches, similar to that described by Carlsson and Stankiewicz (1991), according to whom technology is a “flow of knowledge and competences”. Knowledge is the basis of technological systems and operates as a means to differentiate them. On this subject, the economists make a fundamental distinction between codified knowledge and tacit knowledge (Polanyi 1983). Codified knowledge is explicit, and can easily be the object of transactions through a medium (for example, a patent) which carries it. Tacit knowledge comprises know-how that is often associated with an individual or an organization, which renders commodification more difficult.
Even codified, technological knowledge is not transferred as simple information. There are costs involved in the acquisition of unformalized knowledge and organizational competences required for its use (Mansfield 1998). While the study of knowledge is instrumental to understanding technological systems structuring, the analysis is expected to capture, beyond its formal part, the informal aspects that are necessarily associated with it.
A rich economic literature explores the dissemination of knowledge and, following the above presentation, that of technology. Examining this literature in order to analyze dual technological innovation seems worthwhile. The majority of empirical studies on this subject involve patent data. These data related to knowledge flow identification are validated by a wide diversity of application fields. They were notably used to identify geographical transfers of knowledge (Jaffe et al. 1993; Autant-Bernard and Massard 2000; Autant-Bernard et al. 2014) and knowledge flows within research (Ham et al. 1998). Some used them to capitalize on innovation spin-offs (Trajtenberg 1990) or to study the role played by inventors in knowledge transfers (Jaffe 2000). Finally, many works utilizing patent quotations as analysis instruments examine knowledge or economic spin-offs from public research (Jaffe and Trajtenberg 1996; Henderson et al. 1998).
The analysis of technological dissemination between the defense sector and the civilian sector, either within the well-defined framework of duality or within the broader one of technology transfers, involves patent data only to a limited extent. When employed by defense economists, patent data are mainly used to describe the situation within the field itself (Gallié and Mérindol 2015). The works of Chinworth on duality in Japan (2000a, 2000b) are worth mentioning. Using a more thorough and regular approach, the works of d’Acosta et al. (2011, 2013, 2017) deal with duality, and more broadly with technological innovation in the field of defense, using patent data and an approach based on technological classes.
Less directly related to duality, other works using patent data take into account the defense theme in their analyses to show, for example, that technology transfers from public R&D to the market sectors are influenced by the defense character of innovations (Chakrabarti et al. 1993; Chakrabarti and Anyanwu 1993).
In this book, in order to study dual technological innovation through knowledge, two theoretical frameworks are employed. The first is the coherence framework. It was introduced in the 1990s by the works of Teece et al. (1994), who studied company diversification strategies. Coherence analyses originally dealt with the connection between production operations within a company. They were subsequently adapted and enhanced in order to assess the technological coherence of diversified companies (Piscitello 2005), industrial sectors (Krafft et al. 2011) and technological programs (Avadikyan and Cohendet 2005). These studies facilitate the understanding of how knowledge gets structured.
The second framework is the dominance framework. Economic dominance theory (EDT) is used to explore asymmetric relations between various entities interacting in a network. EDT originates in the works conducted by Perroux (1948) on the power between regions and nations in international exchanges. EDT employs a tool, namely influence graph theory (IGT; Lantner 1974), which identifies the dependences and interdependences between entities.
According to Lantner, IGT facilitates the assessment, within any structure that can be represented by a linear system, of the “global” influence that an entity A exerts on an entity B. But the study of this global influence requires consideration of what happens in the rest of the structure. The connections between A and C, D, etc., impact and amplify the direct influence on B (Lantner and Lebert 2015). In this study, IGT is applied to technological knowledge flows in order to better understand their dissemination between civilian and defense sectors.
Adopting a systemic approach, this work reconciles a global analysis framework centered on the concept of duality (Guichard and Heisbourg 2004; Mérindol 2004; Bellais and Guichard 2006; Serfati 2008) with an approach of technologies (Pinch and Bijker 1984; Carlsson and Stankiewicz 1991; Carlsson et al. 2002; Bijker 2010) facilitating the evaluation of their dual potential. The empirical work relies on the systematic analysis of knowledge production (Jaffe 1986; Jaffe and Trajtenberg 2002; Verspagen 2004; Hall et al. 2005) within large defense companies. It employs tools originating in the theory of technological coherence (Teece et al. 1994; Cohen 1997; Piscitello 2005; Krafft et al. 2011; Nasiriyar et al. 2013) and also those resulting from EDT (Perroux 1948, 1973, 1994; Defourny and Thorbecke 1984; Lantner 1972, 1974; Lantner and Lebert 2015; Lebert 2016; Lebert and Meunier 2017).
This leads to a reflection
