Innovation Ecosystems in the New Economic Era

1. Definition of innovation ecosystems

The modern era is marked by a decrease in the share of tangible capital in favor of intangible capital. This evolution is mainly stimulated by investments in training, R&D, and dissemination of knowledge (David & Foray, 2002; Laperche & Uzunidis, 2007). The research field of the knowledge economy is particularly well suited to the analysis of this dynamic. Indeed, the knowledge economy emphasizes intangible elements related to the production of knowledge, scientific contributions, technical skills, and “human capital” (Foray, 2013). Moreover, information as an intangible asset has also been at the center of the digital revolution, shaping much of economic evolution for several decades. This informational and digital revolution involves a restructuring of economic actors around the generation, storage, processing, and transfer of information (Grange & Sponem, 2021). With its roots in the industrial boom of the 1960s, during the 1980s the informational and digital revolution allowed the introduction of new technologies that support or replace activities that had previously been performed solely by humans (Boccara, 2016; Grange & Sponem, 2021). Thus, the information and communication technologies arising from the digital revolution are laying the foundations of a new network economy (Muet, 2006), the knowledge economy being correlated with these innovative processes.

Indeed, innovation is the key factor in this new context, conditioning the prospects for economic growth (Uzunidis, 2008a), and this at the macro, meso, and micro-economic levels. In its organizational and service forms, it also contributes to the social dynamics of innovative territories (Mongo, 2021).

Relating to the Oslo Manual (2018), “Innovation refers to a new or improved product or business process (or combination thereof) that differs significantly from the unit’s previous products or processes and that has been commercialized or implemented by the firm” (OECD, 2018).

From a theoretical point of view, the problem of innovation has been the subject of an abundant literature aimed in particular at characterizing its conditions of emergence. Initially developed by Schumpeter (1939), the analysis of innovation processes has gradually evolved from an individualistic and linear vision to a more systemic one. Indeed, innovation process is now mainly expressed in terms of a “system”, characterized in particular by its capacity for change, especially technical, managerial, and organizational. It is connected to a complex set of innovation actors constituting an innovation ecosystem (Laperche et al., 2019). There is no single definition of innovation ecosystems. In a recent review of nearly 120 publications on innovation ecosystems, Granstrand & Holgersson (2020) identify 21 definitions of innovation ecosystems. Based on these definitions, the authors conclude that: “An innovation ecosystem is the evolving set of actors, activities, and artifacts, and the institutions and relations, including complementary and substitute relations that are important for the innovative performance of an actor or a population of actors”.

In addition, innovation ecosystems can be generated at different scales.

At the macro-economic level, it is the National Innovation System (NIS) that forms the innovation ecosystem (Laperche et al., 2019). In this framework, innovation results from the connection and interactions between different actors (notably institutional, political, research, and economic) in the same country (Bengt-Åke, 2007) and for which innovation dynamics are at work (Laperche & Uzunidis, 2007). The meso-economic level is characterized by a Local Innovation System (including regional innovation systems, industrial districts, and innovative environments) in which the relationships that link the different actors of the system have a very strong operational dimension (Uzunidis, 2008b). Sectoral systems can be added that link the institutional representatives of a profession (in particular professional unions) with public authorities and companies. These interconnections between actors contribute to the territorial dynamics of innovation (Breschi & Malerba, 1998). Finally, the micro-economic level refers to an innovation system centered on the firm. In this system, companies form a coalition around the pivotal actor who has succeeded in imposing his standard, while at the same time creating value for his partners through processes of coopetition (which combine both competition and cooperation, in particular through subcontracting and co-contracting activities). In this context, we speak of a business ecosystem (Moore, 1993; Boutillier et al., 2015).

These different innovation systems can be interconnected and lead to the formation of innovation networks in which actors interact through processes of “translation” referring to the sociology of innovation (Callon, 1986).

2. Definition of the digital age in relation to the challenge of planet protection

Innovations linked to the digital sector are notably the vector of the Fourth Industrial Revolution. This digital revolution is notably allowed by the new steps of: the processing power of computer chips, IT devices progress, Artificial Intelligence, 3D printing, quantum computing, and an always greater interconnection of vast and faster networks, from Internet to 5G and the Internet of Things. In relation to this, the Fourth Industrial Revolution generates a whole multitude of innovative applications, transforming everyday life, and which is notably related to an almost unlimited economic potential.

These innovative applications building on IT contain major assets to provide solutions to planetary, environmental, and care issues that include global warming, a shortage of non-renewable resources, a better consideration of social and geographical inequities, and better access to health care. Regarding e-health and bio-medical progress driven by digital technologies, Artificial Intelligence is already interpreting MRI with a previously unknown precision. This innovation permits the preventive detection of infinitesimal signs of diseases, such as tumors in their first stages, which could not be detected by MRI human interpretation. In addition, innovations of robotics and Augmented Reality applied to the medical sector are already improving the efficiency of surgery tasks.

Among the innovative applications of the Fourth Industrial Revolution are those related to computer processing of the increasingly massive digital information deposits of Big Data. Advances in digital data treatments generate huge ranges of new services. These include smart-city and transport, to optimize the fluidity of travel, and thus to combat CO2 emissions. Artificial Intelligence is a key for enabling autonomous transport and cars. Also e-agriculture, which builds on the robotization of agricultural machinery and drones to manage agricultural fields with less water and resources. Multiple agricultural devices can be linked together with the Internet of Things and satellites. There is a need for a rationalized consumption, which is less polluting, being processed by Big Data, as well as short circuits that are compatible with the conservation of the Earth’s resources. Innovative smart sensors also contribute to the optimization of resources. Smart factories linked to digital applications will also provide better production management, in a more ecological and less resource-intensive way. The innovative concept of a digital twin allows us to simulate, in the virtual world, production requirements and impacts, for their optimization in the real world. The related flexibility of production will allow consumers to become end-user organizers for more sustainable on demand products. Furthermore, smart factories, through digital technology and 3D printing, will be integrated locally, with a view to establishing short circuits, and reducing the transport of goods and therefore of the linked pollution. Cloud Computing, which also allows on demand access to computing resources, has already generated a reduction in resources compared to a sector that would have produced additional occurrences of similar treatment, and therefore pollution. Thus, the current innovations of Green Computing aim to make this Fourth Industrial Revolution even more resource-efficient. In that way, IT devices can become less and less energy consuming and have a lower carbon footprint. This affects even the new cryptocurrencies, and related blockchain processes using planet-friendly technologies and resources.

Thus, this digital revolution will improve an efficient and ecological way to preserve the planet. And as we will see, related innovation ecosystems have a key role to contribute and accelerate this progress.

3. Importance of ecosystems in the era of digital and ecological transition and their particularities

The current era of digital – as in the age of the new scientific and technological revolution – has changed the way knowledge is explored and produced. The increasing connectedness and interdependence in the digital era has impacted on how knowledge is produced: the creation and dissemination of new knowledge happens in a much more distributed manner. It is not only more collaborative, but also more oriented toward transdisciplinary and interdisciplinary knowledge production (Gibbs, 2015). Given the importance of knowledge in the digital era, the majority of business has recognized that they must invest all their efforts and resources in developing new and innovative ideas. To be successful, the knowledge creation process, as well as innovation activities, thanks to the digital revolution, should be more “open”. This reality, in turn, raises the importance of the ecosystem, especially business ecosystems.

The concept of the ecosystem, borrowed from biology, refers to “a group of interacting companies that depend on each other’s activities” (Jacobides et al., 2018, p. 2256). Assessing an ecosystem at the level of companies, the development of a business ecosystem is more likely to depend on “open” and “collective” innovation (Chesbrough, 2003; Uzunidis, 2018). Digital transformations underway in our societies have largely disrupted the conditions of formation, organization, and deployment of innovation systems. Innovation can emerge and be marketed inside and outside the boundaries of the company through outside-in and inside-out strategies of open innovation and coupled with open innovation. In the age of digital technologies, innovation should be nurtured within an ecosystem meant for the co-creation of value through collaboration. The novelty-generating interactions and collaborations in a business ecosystem all aim at reinforcing the knowledge capital of companies (Laperche, 2017).