The Unmet Need

We are not on track to achieve the universal
agendas targets by 2030-2050 within weak
Socio-Technical Innovation Systems (STIS)

The United Nations High Level Political Forum, HLPF-2019, on Sustainable Development

The world is not on track to achieve the SDGs by 2030 unless the international community steps up the speed and ambition of its actions
Countries must pursue the SDGs as systems, fully recognizing the interconnections between sectors, countries and governance levels, from the global to the local
The shared view is that the global response is not yet transformative enough. Most of the 21 goals to be achieved by 2020 are unlikely to be met.
Unequal access to scientific data and knowledge systems is a major obstacle to the universal implementation of the 2030 Agenda
Governments cannot do it alone; they strive to forge new partnerships with civil society, businesses and the scientific and technological community
Through the Political Declaration of the Summit on the SDGs, Heads of State and Government pledged to make 2020-2030 a decade of action and achievement

The Prerequisite

Achieving the targets need strong
Socio-Technical Innovation Systems (STIS)

“Without Innovation, we Cannot Meet the Challenges of our Time” – November, 2019

United Nations (UN) Secretary-General Antonio Guterres

“The 17 Sustainable Development Goals (SDGs) demand nothing short of a transformation of the financial, economic and political systems that govern our societies today…” – July, 2020

“The Science is Clear. The People are Clear. This is no Time to Procrastinate. The Decisions Taken Over the next few Months and Years will have Enormous Impact on where we will be by 2030″ – Sept 18, 2020

United Nations (UN) Secretary-General Antonio Guterres

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Sustainable Development is Innovation

The earliest innovation roots of development can be traced back to the use of stone tools and obsidian dyes as well as the development of social networks connecting members of our species in large numbers and over long distances dating back to 320,000. -500,000 years in East Africa (Brooks et al., Potts et al., Deino et al., Science; March 2018). The creation and maintenance of these networks required considerable technological, social and cognitive complexity that helped distinguish the early Homo sapiens from other hominid species.

What factors have stimulated this development? Studies show that the major change in early human behavior coincided with a massive change (~ 85%) in mammalian species and a prolonged period of strong climatic and geological changes characterized by pronounced instability of resources and episodes of scarcity. Incorporating various sources of environmental data, this research advances the idea that these upheavals have triggered evolutionary change by promoting technological innovation, travel over longer distances and greater connectivity between social groups as a means of adaptation to scarce and unpredictable resources and as an important survival tool.

Brooks, A.S., Yellen, J.E., Potts, R., Behrensmeyer, A.K., Deino, A.L., Leslie, D.E., Ambrose, S.H., Ferguson, J., d’Errico, F. Zipkin, A.M., Whittaker, S., Post, J., Veatch, E.G., Foecke, K., Clark, J.B., 2018. Long-distance stone transport and pigment use in the earliest Middle Stone Age. Science

Deino, A.L., Behrensmeyer, A.K., Brooks, A.S., Yellen, J.E., Sharp, W.D., Potts, R., 2018. Chronology of the Acheulean to Middle Stone Age Transition in Eastern Africa, Science

Potts, R., Behrensmeyer, A.K., Faith, J.T., Tryon, C.A., Brooks, A.S., Yellen, J.E., Deino, A.L., Kinyanjui, R., Clark, J.B., Haradon, C., Levin, N.E., Meijer, H.J.M., Veatch, E.G., Owen, R.B., Renaut, R.W., 2018. Environmental dynamics during the onset of the Middle Stone Age in eastern Africa, Science

Innovation happens in systems not in silos

Innovation is seen as the result of new knowledge and information obtained from cumulative and evolving processes that mobilize various sources of knowledge. This conceptualization of innovation centers on the interactive and systemic nature of the process (Edquist, 1997; Lundvall, 1992). Unlike the neoclassical approach which defined innovation as the result of a sequential and technocratic process and corresponded to a purely technical act based on the production of a new product, the new conception of innovation promotes a vision that integrates technical change into more global changes.

Innovation is a cumulative process of solving problems that involve different forms of learning, the most famous of which are learning through research, through practice, through the use of advanced techniques, through interaction, through industrial externalities. and by regional externalities.

Taking its meaning throughout the economy and society, innovation is also a social process between different actors within a given environment (Asheim and Isasken, 2002). The interaction of the different actors is at the origin of a system effect mobilizing different knowledge bases according to the actors and therefore conditions the possibilities of innovation.

Innovation is also a process based on close relationships, favorable conditions for interactions and learning with a view to exploring new combinations of knowledge and opportunities (Maskell and Malmberg, 1999). It is intimately linked and stimulated by geographical proximity, which makes it possible to increase the interactive capacity of forms of learning by facilitating the relationship between the innovative organization and the external inputs that are necessary during the innovation process. Therefore, national innovation systems are seen as the result of regional innovation systems. A regional innovation system refers to spatial concentrations of companies and public and semi-public organizations (universities, research institutes, technology transfer and liaison agencies, business associations, government bodies, etc.) which produce innovation on the basis of interactions and collective learning through common institutional practices. According to this perspective, the regional innovation system is intimately linked to the knowledge economy and to the new conception of innovation as the result of a social and territorial product, stimulated not only by locally anchored resources but also by social and cultural context in which it operates (Bathelt et al., 2004).

Asheim, B.T et Isaksen, A. (2002) Regional Innovation Systems: The Integration of Local ‘Sticky’ and global ‘ubiquitous’ Knowledge. Journal of Technology Transfer, 27, 77-86.

Bathelt, H., Malmberg, A., Maskell, P., 2004. Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography 28 (1), 31–56.

Edquist, C., (1997) Systems of Innovation: Technologies, Institutions and Organizations. Pinter, London.

Lundvall, B-A. (1992) National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning. Pinter, London.

Maskell, P. et Malmberg, A. (1999) Localised learning and industrial competitiveness. Cambridge journal of economics, 23(2), 167-186.

Innovation Systems Functions (SI)

The innovation systems approach considers the ‘business ecosystem’ of an innovating organisation and analyses the flow of information and technology as well as the interactions and relationships between the actors involved, such as enterprises, research institutions and the central and local governments.

A number of key functions have been identified that are essential for the proper operating of an IS. Several variations of IS frameworks have been developed by different authors, ranging from models that differentiate seven key processes to models that identify nine key processes. However, in essence these models have all been based on the same set of seven dynamic functions which are described by Bergek et al., (2008) :

1- Knowledge development and diffusion
This is the function that is normally placed at the heart of an innovation system in that it is concerned with the knowledge base of the global system and how well the local system performs in terms of its knowledge base and, of course, its evolution. The function captures the breadth and depth of the current knowledge base of the innovation system, and how that changes over time, including how that knowledge is diffused and combined in the system.
2- Influence on the direction of search
If a TIS is to develop, a whole range of firms and other organizations have to choose to enter it. There must then be sufficient incentives and/or pressures for the organizations to be induced to do so. The second function is the combined strength of such factors. It also covers the mechanisms having an influence on the direction of search within the TIS, in terms of different competing technologies, applications, markets, business models etc…
3- Entrepreneurial experimentation
An IS evolves under considerable uncertainty in terms of technologies, applications and markets. This uncertainty is a fundamental feature of technological and industrial development and is not limited to early phases in the evolution of an IS but is a characteristic of later phases as well. From a social perspective, the main source of uncertainty reduction is entrepreneurial experimentation, which implies a probing into new technologies and applications, where many will fail, some will succeed and a social learning process will unfold.
4- Market formation
For an emerging IS, or one in a period of transformation, markets may not exist, or be greatly underdeveloped. Marketplaces may not exist, potential customers may not have articulated their demand, or have the capability to do so, price/performance of the new technology may be poor, uncertainties may prevail in many dimensions. Institutional change, e.g. the formation of standards, is often a prerequisite for markets to evolve from “nursing markets” to a “bridging market” up to mass markets.
5- Legitimation
Legitimacy is a matter of social acceptance and compliance with relevant institutions: The new technology and its proponents need to be considered appropriate and desirable by relevant actors in order for resources to be mobilized, for demand to form and for actors in the new IS to acquire political strength.
6- Resource mobilization
As an IS evolves, a range of different resources needs to be mobilized. Hence, we need to understand the extent to which the IS is able to mobilize competence/human capital through education in specific scientific and technological fields as well as in entrepreneurship, management and finance, financial capital (seed and venture capital, diversifying firms, etc.), and complementary assets such as complementary products, services, network infrastructure, etc.
7- Development of positive externalities
The systemic nature of the innovation and diffusion process strongly suggests that the generation of positive external economies is a key process in the formation and growth of an IS. These external economies, or free utilities, may be both pecuniary and non pecuniary.

Bergek, Anna, Staffan Jacobsson, Bo Carlsson, Sven Lindmark, and Annika Rickne. 2008. “Analyzing the Functional Dynamics of Technological Innovation Systems: A Scheme of Analysis.” Research Policy 37 (3): 407–429. 

Innovation Processes

For the past fifty years, new methods promoting innovative design have flourished: CK theory, Project management by issues, Design Thinking, Lean Startup, Business Model Canvas, Lean Canvas, Outcome Driven Innovation among others…

The methodological diversity of concepts promoting innovation offers the possibility, depending on the problem to be dealt with and its environment, to favor a particular method or to draw from their complementarities.

Obviously other factors such as the organisation’s culture or the saturation of the relevant market come into consideration in making the most judicious methodological choice. The choice to be made from this range of solutions also applies to managers. Depending on the strengths and weaknesses of their department, they can choose the method (s) that will make their team more efficient and its results more relevant for the entire organisation.

Louis Bouwer from the Innovation Management Research Institute (IMRI) published in 2017 the “Innovation Management Theory Evolution Map” to help innovation managers take note of existing fundamental innovation management theories, how they evolved through the past few decades and which theories are best suited to solve specific corporate innovation management challenges.

Louis Bouwer (Innovation Management Research Institute, IMRI); The Innovation Management Theory Evolution Map