SME segmentation and regional development agencies’ innovation support measures

Abstract

The purpose of this paper is to substantiate the necessity and technical possibilities of creating a coherent and intelligent digital tool for small and medium-sized enterprises’ (SME) segmentation, with the support of regional development agencies’ (RDAs) databases. This tool would allow RDAs to improve the monitoring of the financial and innovation support mechanisms for SMEs and enable a classification of the regional population of SMEs in the specific interest categories, such as Regional Innovation Strategies for Smart Specialisation (RIS3). As a result, the digitally supported methodology described in this paper contributes to enhancing the effectiveness and efficiency of regional support by analysing the impact of the received aid on the productivity of the innovative SMEs. Additionally, the paper provides a categorization of their industrial activity at a more detailed level. Finally, it is argued that those companies with the highest innovation potential could benefit the most from enhanced segmentation. Providing RDAs with data-driven decision tools means that more tailor-made innovation-support instruments can be designed (as opposed to unspecific support instruments). Moreover, the tools could make it easier to perform impact assessment (to justify the investment), from both a qualitative (e.g., a classification based on companies’ assets and merits in key areas for the region) and a quantitative (e.g., financial performance and indicators) point of view.

Keywords

• funding
• innovation policy
• regional innovation support
• regional development agencies
• small and medium-sized enterprise segmentation
• data-mining