Project Overview

Industrial innovation has changed fundamentally over the last ten years. The science, technology or corporate-driven innovation paradigm has been challenged by a new open, human and eco-system-based collaborative innovation paradigm since the 1990’s. Companies have widely adopted new tools such as open innovation, innovation networks and ecosystems, systemic innovations, public/private partnerships, crowd sourcing, social media, and demand based innovations.

Fundamentally IIT has helped realizing the innovation-based growth strategy for Europe through stimulating the modernization of current practices of innovation management. The objective has been to improve the innovation performance of European companies and the effectiveness of innovation policy instruments in order to generate new growth and jobs in Europe.

The project has examined the current level of new innovation tool adoption in European companies through in-depth interviews with 800 companies ranging from innovation leaders to followers in different parts of Europe. The results are now being disseminated globally for example in collaboration with the European Round Table (ERT), Orgalime and other major institutions and initiatives active in the European RDI landscape.

The current innovation policy tools in Europe have been assessed through policy review and workshops with national and regional stakeholders. The results are summarized as recommendations for drafting future policies for innovation, especially in industrial domain in the Key Deliverables of the project (see Key Deliverables).

In order to maximize the return on investment for the project, a research toolbox has also been created for Member States and the EC for replicating this study. The toolbox provides a step-by-step guide for investigating the current state of innovation process adoption, and for analyzing how the current innovation promotion portfolios could be developed to respond to the needs of industrial companies.


Partners

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 649351