Literature on Innovation Systems
Some IPPPs, as a sub-group of the PPINs, are part of a productive and local innovation dynamic. The IPPPs are generally, but not exclusively, developed within a country. Studies relating to national innovation systems (Nelson, 1993) are applied to the innovation dynamics of these IPPPs. Freeman (1987) defines the NIS as the network of institutions in the public and private sector which allows new technologies to be modified and disseminated. Indeed, one of the indicators used to measure the existence of regional innovation systems is the creation of a company by university researchers (Djellal, Gallouj, 2010). Several OECD reports compare the efficiency of member countries’ NISs, and integrate case studies involving IPPPs (OECD, 1999, 2001b, 2003). The OECD points out that the use of PPPs differs according to country, and indicates that, in general, a better use of the research PPPs increases the synergies between the market and research (OECD 1999).
This systematic decoupling not only concerns national innovation systems but it can be seen in regional innovation systems, local innovation systems, technological or sectoral innovation systems. The PPINs are therefore the basis of these innovation systems (Depret, Hamdouch 2009; Djellal, Gallouj, 2010). The dynamics of learning, of absorption capacity, of economies of scale and of scope or of agglomeration, transaction costs, questions of positive externalities or network externalities, the appropriation and dissemination of knowledge are addressed here. This is also true of studies which are more broadly linked to the dimensions of physical, cognitive, organisational, social, institutional proximity (Boschma, 2005; Rallet, Torre, 2007; Bouba-Olga, Grosseti, 2008).
Of the systematic studies which are potentially about IPPPs, particular mention should be made of the “triple helix” model (Etzkowitz, Leydesdorff, 2000), of the “entrepreneurial university” (Clark, 1998), as well as the new production of knowledge (Gibbons et al., 1994). These knowledge development models are distinguished by their approach to change. Although the triple helix model suggests a historical continuity in the model of university development, Gibbons et al. (1994) sense a change in the way in which scientific knowledge is organised and transferred today, compared with the relationship which previously existed between the university world and society. They make the distinction between the method of producing knowledge before 1950, in which there was a division between the university world and society, and the new mode of knowledge production, which, in particular, involves a new interdisciplinarity, considerable researcher mobility, the formation of temporary groups of experts, or the primacy of economic and social problems in the decision to develop a particular sphere of knowledge (Shinn, 2002).
According to Etzkowitz (2003), the university was given the task of “economic and social development,” in addition to its two initial tasks (teaching and research). This third task formed part of a second university revolution, which transformed centres of research into quasi-enterprises. Activities were developed that were common to public and private institutions, and these led to hybridisations. This development led to organisational problems, which were mainly linked to conflicts of values between the university and the entrepreneurial spirit, such as the incompatibility of the university’s missions, responsibilities, expectations and resources (Sotirakou, 2004; Gierding et al., 2006). Learning would allow these institutions to adapt to constant change and to merge different rationalities (Gjerding et al., 2006). In order to be entrepreneurial, the university should have an organisational culture that favours the spirit of enterprise, and accept risk-taking.
University practices and entrepreneurial contexts differ depending on the country (Gjerding et al., 2006; OCDE, 2001 a, b). Thus the legal framework, and in particular the way in which the State organises the commercialisation of public research, has a strong influence on the forms in which public research is transferred to enterprises (and therefore on IPPPs). The Bayh-Dole Act,  The Bayh-Dole Act led to the formation of structures... adopted in 1980 in the United States, or the July 12 1999 law on innovation in France, improved the use of research results (Philippart, 2003). This kind of law helps to speed up the process, moving from the idea to the product (Laperche, 2002). As part of the 1999 law, public researchers alternately or simultaneously adhere to private sector operating rules (such as the requirement for a result, the emphasis placed on applied research, the demands of the market), while continuing to belong to the public institution  The law of July 1999 allows public researchers to move.... These laws favour the creation of enterprises by researchers, transforming them into “new scientific entrepreneurs” (Etzkowitz, 1998; Laperche, 2002). According to Laperche (2002), innovation policies are not sufficient to explain the process of commercialising research. Four key factors are identified for the commercialisation of research (described as the organic square of commercialisation): “regulations,” “university strategy,” “technical progress,” as well as “the economic milieu and the spirit of enterprise”.
R&D and innovation policies are inspired by these advances in the literature. Those responsible for research policies, who initially supported investment in R&D, are questioning the effectiveness of this support and making it conditional on results, focusing resources on specific contracts (OECD, 1998; Laperche, 2002). Finally, little by little, innovation clusters have become the preferred means of public action to support national competitiveness (Porter, 1998; OECD, 2001b; Forest, Hamdouch, 2009).
Studies on clusters (or on innovative milieux, technological districts, science and technology parks) have developed significantly in the last twenty years. These studies reveal a growing interest in the phenomena of localisation, industrial organisation and the dissemination of innovation (Leroux, Berro, 2010; Krugman 1991; Brezis et al., 1993; Porter, 1998). They help to understand the innovation process in IPPPs in several respects: the creation of an IPPP can be linked to the emergence of a cluster but, more frequently, the partners use the opportunities associated with this industrial policy (benefiting from the visibility that membership of a cluster provides), to obtain funding for their project (in particular venture capital)  The alliances between enterprises and universities..., and to benefit from additional resources and innovation dynamics linked to already existing clusters (dissemination of knowledge, the search for economies of scale, technological externalities and, more broadly, economies of agglomeration) (Catherine, Corroleur, 2001; Forest, Hamdouch, 2009).
Some of the literature on clusters analyses the relationships of cooperation and competition between the partners. This research concerns the way in which public and private actors interact and liaise, thus encouraging the development of specific scientific or technological local or regional spaces (Hamdouch, 2008; Forest, Hamdouch, 2009). These approaches concern the role of the star scientists in creating enterprises (Mangematin et al., 2003; Carpentier et al., 2007; Leroux, Berro, 2010). Indeed, a section of the IPPPs, between a public researcher and the private sector, is initiated by the star scientists (Zucker, Darby, 1996), or serial entrepreneurs, in other words partnerships whose development is explained by the researcher’s personality and scientific skills (Catherine, Corroleur, 2001). These skills should, however, be combined with managerial skills, which these researchers acquire from the private sector, which explains the creation of the IPPP.
In the health sector this literature focuses mainly on the High-Tech sectors. But these sectors are characterised by their high level of R&D, the development of new technological trajectories, as well as the development of radical innovations (Zeller, 2001; Cooke, 2002; Depret, Hamdouch, 2009). Consequently these studies do not take into account all cases of IPPPs, as some IPPPs in the health sector are based on a less “ambitious” project, such as the acquisition or sharing of innovative equipment, the purpose of which is directed more at reducing costs than at a logic of knowledge production. The literature on clusters distinguishes industrial clusters from innovation clusters  The innovation clusters are “a set of organisations.... In innovation clusters the emphasis is not on the economies associated with production, but on networks of innovation which allow the dissemination of explicit or tacit knowledge (Forest, Hamdouch, 2009).
This kind of disassociation (cost reduction vs. knowledge dissemination) could be used to differentiate the IPPPs depending on the object of the innovation which is the focus of the contract (for example the simple adoption of technological innovation, or the formation of an innovation network), and could therefore supplement the criteria which we present in the following point.