Research on SME innovation especially in traditional manufacturing regions Part 2

By Prof Geoff Pugh and Prof Jon Fairburn

Part 1 of this article can be found here

  • Radicic, D., Pugh, G. and Douglas, D. (2018). Promoting cooperation in innovation ecosystems: Evidence from European traditional manufacturing SMEs, Small Business Economics. Accepted 01-08-2018.


We investigate whether public support for innovation increases the propensity of SMEs in traditional manufacturing industries to cooperate for innovation—in particular, for incremental innovation—with other firms and external knowledge providers. Using data from seven EU regions, we find that support programmes do not promote cooperation with competitors, marginally promote cooperation with customers and suppliers and strongly promote cooperation with knowledge providers. These findings suggest that, in this case, the role of public policy is systems conforming rather than systems creating. Innovation support programmes can assist SMEs in traditional manufacturing industry to consolidate and/or extend their innovation ecosystems beyond familiar business partners by promoting cooperation with both private and public sector knowledge providers. Finally, our findings suggest that evaluation studies of innovation support programmes should be designed to capture not only input and/or output additionality but also behavioural and systemic effects.


SMEs; Traditional manufacturing industry; Innovation ecosystems; Innovation policy; Cooperation for innovation; Behavioural additionality 

  • Radicic, D., Douglas, D., Pugh, G. and Jackson, I. (2018). Cooperation for innovation and its impact on technological and non-technological innovations: empirical evidence for European SMEs in traditional manufacturing industries, International Journal of Innovation Management. Accepted 07-09-2018.


Drawing on a sample of small and medium-sized enterprises (SMEs) in traditional manufacturing industries from seven EU regions, this study investigates how cooperation with external organisations affects technological (product and process) innovations and non-technological (organisational and marketing) innovations as well as the commercial success of product and process innovations (i.e., innovative sales). Our empirical strategy takes into account that all four types of innovation are potentially complementary. Empirical results suggest that cooperation increases firms’ innovativeness and yields substantial commercial benefits. In particular, increasing the number of cooperation partnerships has a positive impact on all measures of innovation performance. We conclude that a portfolio approach to cooperation enhances innovation performance and that innovation support programs should be demand-led.

From the MAPEER project:

  • Radicic, D. and Pugh, G (2016).  R&D programmes, policy mix, and the “European Paradox”: evidence from European SMEs, Science and Public Policy, 44 ( 4 ) ( 2017 ), pp. 497 – 512. doi: 10.1093/scipol/scw077. First published online: October 2, 2016.


Using a sample of small and medium-sized enterprises from twenty-eight European countries, this study evaluates the input and output additionality of national and European Union (EU) R&D programmes both separately and in combination. Accordingly, we contribute to understanding the effectiveness of innovation policy from the perspective of policy mix. Empirical results are different for innovation inputs and outputs. For innovation inputs, we found positive treatment effects from national and EU programmes separately as well as complementary effects for firms supported from both sources relative to firms supported only by national programmes. For innovation outputs, we report no evidence of additionality from national programmes and cannot reject crowding out from EU programmes. However, crowding out from EU support is eliminated by combination with national support. These findings have policy implications for the governance of R&D policy and suggest that the European paradox—success in promoting R&D inputs but not commercialisation—is not yet mitigated.

Key words: R&D support; SMEs; policy mix; input and output additionality; European paradox

  • Radicic, D. and Pugh, G. (2017). Performance Effects of External Search Strategies in European Small and Medium-Sized Enterprises. Journal of Small Business Management, 55, 76-114. First published on-line: Feb.15th 2017.                                      


There is little evidence regarding the performance impact of open innovation on small and medium-sized enterprises (SMEs), especially across different firm-size categories and sectors. Using new survey data from 28 European countries, we specify ordered logit and generalized proportional odds models to explore how seven individual external search strategies (knowledge sources) affect SME innovation performance across different size categories and sectors. While we find some consistently positive effects, in particular from using customers as an external knowledge source, we also find that some search strategies may not be beneficial. These findings suggest managerial and policy implications.

  • Radicic, D. (2020). National and international R&D support programmes and technology scouting in European small and medium enterprises. Journal of Science and Technology Policy Management 11(4), 455-482.


Purpose. This study aims to evaluate the effectiveness of national and international R&D support programmes on firms’ technology scouting, defined as firms’ use of external knowledge sources.

Design/methodology/approach. Drawing on a unique data set on R&D support programmes for small and medium-sized enterprises (SMEs) operating in both manufacturing and service sectors across 28 European countries, this study reports treatment effects estimated by the copula-based endogenous switching model, which takes into account unobserved firm heterogeneity.

Findings. Empirical results indicate that R&D support programmes have heterogeneous effects on technology scouting. In particular, a crowding-out effect arises in the case of informal sources of external knowledge, whereas additional effects are reported for formal, strategic sources.

Practical implications. For informal sources of external knowledge, a random distribution of R&D measures would have a substantially larger effect rather than using current selection criteria.

Originality/value. To the best of the authors’ knowledge, this is the first study to explore the policy effects on technology scouting applying a copula-based endogenous switching model. Most cross-sectional empirical studies use matching estimators, although their main disadvantage is the selection on observables.

Key words External knowledge search; Behavioural additionality; Copula-based endogenous switching model; European SMEs; Technology

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Part 1 of this article can be found here