of economies. The new entrepreneur must be an innovator like their peers and is an integral part of the national innovation system in a knowledge-based economy (see section 1.4). The entrepreneurial society (Audretsch 2007) gradually began taking over from the labor society.
The entrepreneur, who had been sidelined by the managerial company, then made a big comeback by developing new innovations. They act in the sense in which Say understood it, i.e. as an intermediary between the scientist and the worker. The scientist was no longer isolated in an obscure laboratory, as was imagined in the 18th and 19th centuries, but was part of the great scientific laboratories financed by States, often by the army (Isaacson 2015). Young entrepreneurs, poorly endowed with capital, but very imaginative and with a keen sense of business, created industrial empires, giving rise, for example, to what we now refer to as GAFAM (Google, Apple, Facebook, Amazon, Microsoft). The large firm did not disappear, therefore, but took on a new form, favoring subcontracting and cooperative relationships via open innovation (Chesbrough 2003), rather than the model of vertical integration which the managerial firm of the 1950s–1970s was based on, inspired by the legacy of the first Industrial Revolution. The firm has taken the form of a network firm, combining classical integration with multiple cooperative relationships with universities, other competing firms (coopetition), complementary firms (customers and suppliers), start-ups, communities and crowdsourcing (Laperche and Uzunidis 2019). The constitution and development of its knowledge capital (i.e. all the information and knowledge produced, accumulated and systematized by the company with the aim of innovating) is carried out collectively (Laperche 2017). The principle of open innovation offers innovative entrepreneurs, who have become start-uppers, the opportunity to develop cooperative relationships with large companies, as well as with research centers and universities (Audretsch and Link 2017), as put forward with the concept of the “triple helix” (Etzkowitz 2003).
How companies manage their innovation process is a key theme in innovation management. The work of Nonaka and his co-authors, for example, focuses on the genesis and circulation of knowledge in the organization. This is the SECI (socialization, externalization, combination, internalization) model (Nonaka and Takeushi 1995), where innovation in the organization emerges from the interaction between explicit and tacit knowledge, associated with a circulation of knowledge from the individual to the inter-organizational level. Similarly, the C-K theory (which stands for concept and knowledge) focuses on issues of creativity within design and provides further developments on the genesis of knowledge within organizations (Hatchuel and Weil 2009; Le Masson and Macmahon 2016).
This work on the production and dissemination of knowledge within organizations is part of resource theory. The authors place particular emphasis on the role of competencies (especially key competencies (Prahalad and Hamel 1990)) and capabilities in explaining the competitive advantage of firms. Capabilities develop new specific assets gathered in organizational routines, which are called “dynamic capabilities” by Teece et al. (1997). They refer to the “firm’s ability to integrate, build and reconfigure internal and external competencies to respond quickly to changes in the environment”. Among these dynamic capacities, the absorption capacity is central to the analysis of firms’ knowledge capital formation. Absorptive capacity was first defined by Cohen and Levinthal (1990) as the firm’s ability to recognize the value of new information, transform it into knowledge, assimilate it and apply it for business purposes. The firm is then open to its environment, and the management of multiple cooperative relationships is considered a “managerial innovation” (Mignon et al. 2020).
Universities have also transformed themselves to become entrepreneurial and play a more active role in innovation. The economic context, marked by a decline in public funding for research, is contributing to a radical metamorphosis in the work of the researcher who also becomes an entrepreneur, by creating a spin-off, or by filing patents, etc., responding to the injunctions of all up-and-coming entrepreneurs (Lanciano-Morandat 2019). It is also in universities, primarily in the United States, that major transformations are taking place. In the laboratories of the Massachusetts Institute of Technology (MIT), hackers and makers are appearing who will also contribute to transforming production methods, with an entrepreneurial and creative approach.
The first hackers formed a closed club: they are distinguished by their technical prowess. Unlike the Fordist company, which was then dominant, they worked in a collaborative and horizontal way. Each could take the ideas of the other and improve them (Capdevila 2015). This principle was also developed with fablabs at the end of the 1990s, again at MIT (Morel and Le Roux 2016). The objective is to be able to “create anything and everything”. The experiment is bearing fruit. Students do not hesitate to hijack the machines to satisfy their needs. The principle of “Do It Yourself” then takes on its full meaning, even if some people date it back to the end of the 18th century (Berrebi-Hoffmann et al. 2018). The word “hacker” appeared in the mid-2000s (Anderson 2012), to designate a reality that had, in fact, emerged in the United States in the 1960s and 1970s. The phenomenon of hackerspaces became global in the 1980s, and was not limited to developed countries.
In this same trajectory, another phenomenon appeared at the beginning of the 2000s in California, participating in the development of the entrepreneurial society, that of coworking, which is also referred to as the “third place” (Oldenburg 1989). Coworking or collaborative workspace has its origins both in the recent evolution of digital technologies (Lallement 2015; Berrebi-Hoffman et al. 2018) and in the desire of many employees to escape the interventionism of the managerial enterprise with its oppressive rules. The aim is to help “coworkers” develop their creativity and imagination in the absence of any authoritative or hierarchical relationships. Although these coworking spaces bring together a wide variety of people in different situations, they generally aim to offer good working conditions in terms of autonomy of organization, and even conviviality. Coworkers are not subject to working hours. They are not salaried employees but entrepreneurs (or even self-employed), masters of their working hours, but rarely of their income, as many of them work under precarious conditions (Hill 2015). The entrepreneur is plural, competition is severe: many are called, but few are chosen (Aldrich 2011).
The genesis of innovation is thus both a multiple phenomenon and the result of the involvement of a growing number of organizations and economic agents, and not only the expression of a heroic entrepreneur. The recognition of this collective nature of innovation has a strong impact on innovation policies, which increasingly target the functioning of innovation systems at different scales.
1.5. Innovation policies and the innovation system
The term “innovation policy” is relatively new. Initiated in the 1960s by the SPRU (Science Policy Research Unit), it was quickly reappropriated by international organizations in the 1990s (Fagerberg et al. 2011). This evolution is part of a process of major economic transformations that occurred after the end of World War II and accompanied the development of the managerial enterprise. It is linked to the understanding of the innovation phenomena. Indeed, if science policies have been oriented towards the creation of academic knowledge, the training of scientists and fundamental research, technology policies are more related to the commercialization or non-academic valorization of scientific knowledge. In this context, innovation policies have often been reduced to activities related to R&D and scientific activity. However, public innovation management policy is compartmentalized into three broad categories (Sharif 2006):
– Science policy, inherent in the promotion and production of scientific knowledge, representing the allocation of resources between different scientific activities.
– Technology policy, which is based more on technologies used, developed and which are strategic within the economy.
– Finally, innovation policy, which is similar to innovation processes as a whole, based not only on the content of scientific and technical innovations but also on the institutional structure of the economy.
The role of the State in the management of an innovation policy is indeed to design institutional arrangements that allow support for innovation activities and the application of basic research. However, this must be done without compromising the selection