NEW publication on: Implementing smart specialisation - thematic platform on industrial modernisation29 Sep 2017
Ensuring participation and ownership in the S3 Process
The fact that RIS3 is based on a wide view of innovation automatically implies that stakeholders of different types and levels should participate extensively in its design. The perhaps most common, tripartite governance model based on the involvement of industry, education and research institutions, and government (the so-called Triple Helix model), is no longer enough in the context of smart specialisation.
Innovation users or groups representing demand-side perspectives and consumers, relevant non-profit organisations representing citizens and workers should all be taken on board of the design process of RIS3. In other words this means that the governance model includes both the market and the civic society. When it comes to the sensitive moment of deciding on strategic priorities, a truly inclusive RIS3 governance structure should be able to prevent capture by specific interest groups, powerful lobbies, or major regional stakeholders.
In order to secure that all stakeholders own and share the strategy, governance schemes should allow for 'collaborative leadership', meaning that hierarchies in decision-making should be flexible enough in order to let each actor to have a role and eventually take the lead in specific phases of RIS3 design, according to actors' characteristics, background, and capacities.
When actors are many and different, it might be very difficult for them to find their own way to collaborate and manage potential conflicts. In order to tackle this potential problem, RIS3 governance bodies should include 'boundary spanners', that is to say, people or organisations with interdisciplinary knowledge or proven experience in interaction with different actors, and who can hence help moderate the process.
JRC Science for Policy Report Mariussen Åge; Rakhmatullin Ruslan; Stanionyte Lina.
JRC88896 Jens Sörvik and Alexander Kleibrink
Regional benchmarking in the smart specialisation process: Identification of reference regions based on structural similarity
03/2014 Mikel Navarro, Juan José Gibaja, Susana Franco, Asier Murciego, Carlo Gianelle, Fatime Barbara Hegyi and Alexander Kleibrink