The goal of this project is to develop a set of policy instruments for entrepreneurs, managers and public and private-sector decision-makers.  The aim of such instruments is to sustain the growth of those companies operating in the key enabling technologies sectors, as defined within the EU program Horizon 2020 (micro and nano electronics, photonics, nanotechnology, new materials, biotechnology, advanced automation systems, ICT and the space sector). As a matter of fact, several policy documents and reports highlight the fundamental role played by these companies in the conversion of scientific knowledge into new products and processes, in employment growth, especially in the case of highly qualified profiles, and in the consolidation of European competitiveness on the global landscape.

From a conceptual point of view, firm growth is a multi-faceted phenomenon. More specifically, definitions and ideas of growth entail not only meanings related to increases of turnover and employment, but also innovation, internationalisation and attractiveness for investors. Consequently, we will address the phenomenon from three complementary perspectives:

• actors and organisational structures;
• strategies and business models;
• contextual factors.

We argue that firms may grow through a variety of patterns, and, since growth drivers are typically intertwined, simplistic conceptual frameworks should be discarded. Therefore, we aim at formulating a theory of systemic growth, since the main object of our analysis is the dynamic interaction between actors, structures, strategies and processes. Such theory cannot be deterministic, because it assumes that the configuration of actors, structure and context in a given phase of the history of the company may result in multiple growth paths.

To this purpose we will adopt an innovative statistical technique: the fuzzy set analysis. Unlike conventional quantitative methods, such as regression analysis, the fuzzy set analysis does not assume an univocal causal relationship between explanatory variables and results, but it leads to several possible solutions given by consistent combinations of variables.

Our expected results feature many interesting profiles for knowledge advancement in the disciplines of management and may provide the basis for the development of a “new generation” of industrial policies.