Regional innovation policies often encourage the formation of R&D consortia between co‐localised small‐ and medium‐ sized firms (SMEs) and large companies, universities or other agents. We investigate the benefits in terms of labour productivity arising for SMEs from alternative configurations of such consortia. We focus on an Italian regional policy. Using a hierarchical Bayesian approach for inference, we find that consortia work better when they are vertical rather than horizontal, and when they match SMEs to large firms. On the contrary, neither the presence of a university nor that of an innovation intermediary is always associated with higher firms' productivity.

What kinds of R&D consortia enhance SMEs productivity? A hierarchical Bayesian approach for the analysis of a regional innovation policy / Annalisa Caloffi, Marco Mariani, Alessandra Mattei, Fabrizia Mealli. - In: PAPERS IN REGIONAL SCIENCE. - ISSN 1056-8190. - STAMPA. - (2019), pp. 1-29. [10.1111/pirs.12476]

What kinds of R&D consortia enhance SMEs productivity? A hierarchical Bayesian approach for the analysis of a regional innovation policy

Annalisa Caloffi
;
Alessandra Mattei;Fabrizia Mealli
2019

Abstract

Regional innovation policies often encourage the formation of R&D consortia between co‐localised small‐ and medium‐ sized firms (SMEs) and large companies, universities or other agents. We investigate the benefits in terms of labour productivity arising for SMEs from alternative configurations of such consortia. We focus on an Italian regional policy. Using a hierarchical Bayesian approach for inference, we find that consortia work better when they are vertical rather than horizontal, and when they match SMEs to large firms. On the contrary, neither the presence of a university nor that of an innovation intermediary is always associated with higher firms' productivity.
2019
1
29
Goal 9: Industry, Innovation, and Infrastructure
Annalisa Caloffi, Marco Mariani, Alessandra Mattei, Fabrizia Mealli
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1170581
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