A connectivity model as a potential tool for smart specialization strategies

ABSTRACT

The article contributes to the smart specialization literature by presenting a new approach, connectivity analysis, where Triple Helix (TH) relations (involving universities, companies and government) are at the centre of the entrepreneurial discovery process. Relations between helices may be seen, from the point of departure of proximity, as preconditions of connectivity, or interaction, measured through expectations and experiences. This offers potential solution to two limitations of proximity approach: its static nature and narrow focus on dyadic relationships. The connectivity analysis reveals the extent of mutual expectations, as well as tensions, or gaps. Based on this analysis, the article presents a policy model that is used to map structures of networks and gaps between TH actors. It may also identify strengths, weaknesses and problems. This analysis is used as input to structured dialogues between actors in leading positions in the TH and in smart specialization policy-making and implementation. This approach may lead to policy interventions supporting entrepreneurial discoveries. The model has been developed in partnership with researchers and the Regional Council of Ostrobothnia. The article also presents this case study and demonstrates the use of the connectivity model in practice.

KEYWORDS:

• Connectivity model
• entrepreneurial discovery process
• gap analysis
• proximity
• smart specialization
• Triple Helix connectivity

Acknowledgements

We would like to acknowledge the Regional Council of Ostrobothnia, and especially Mr Jerker Johnson, as well as the other members of the research team Smart specialisering strategi Österbotten for co-operation. Åge Mariussen acknowledges the support of Nordland County Council VRI program through the RISCK project. We would also like to thank the two anonymous referees for really valuable comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The optimal proximity could be found by comparing regions and their connectivity measurements (gap index) with other regional performance. Then the optimal level of connectivity can also vary between regions depending on the value of these indicators and other factors.

Additional information

Funding

This work was supported by the Programme for R&D and innovation (VRI) of Norwegian Research Council through the RISCK project (project number 238983/050).