Abstract

We study the underlying mechanisms of technological innovation in SMEs in the context of ex-post evaluation of European Union’s regional policy. Our aim is to explain the observed change in firms’ innovativeness after receiving EU support for technological investment. To do so, we take an approach that is novel in innovation studies: a Bayesian Network Analysis to assess the effectiveness of EU policy instrument for technological innovation and to determine the mechanisms by which the policy works within firms. Our data draw from a unique survey of 200 Polish firms that received “Technological Credit” during the 2007−2013 programming period. First, we confirm the short-term positive impact of the EU innovation policy (i.e. a wider range of products/services offered, increased sales and exports). More importantly, we determine the causal chain between economically quantifiable outcomes and behavioural change in the firm, which is an important node in the network of effects generated. We find that only the financially sounder and more internationalised firms managed to take advantage of the policy. These findings suggest that programmes based on technological credits are not well suited to foster innovation in more fragile and domestically oriented SMEs, which may require different policy instruments.

Highlights

  • This paper studies the mechanisms underlying the observed technological change induced by innovation policy in Small and Medium-sized Enterprises (SMEs

  • Our focus is on Technological Credit (TC), a policy instrument supported by the EU

  • Our analysis focuses on one particular policy instrument, namely Technological Credit, which was selected by the European Commission for in-depth analysis19

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Summary

Introduction

This paper studies the mechanisms underlying the observed technological change induced by innovation policy in Small and Medium-sized Enterprises (SMEs). Our research question is linked to the so-called “black-box” problem of policy intervention (Astbury & Leeuw, 2010; Brown & Mason, 2014) and the possible mismatch between the ways in which policymakers and participating firms view the relevant EU policy measures (Massa & Testa, 2008)6 Comparable empirical evidence for firms in the new EU member states is lacking, apart from the study on Hungarian companies by Béres and Závecz (2016)

Cross-country analysis also tends to focus on the Western European experience
Innovation in Polish firms and constraints on technological investment
The evaluation strategy
Bayesian Network Analysis as a tool for ex-post policy evaluation
The survey data
I have decreased total costs
The BNA results
Understood importance of having more younger employees
Education
Test of the theory behind the intervention
Findings
Conclusions and policy implications
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