Geographical clustering and the effectiveness of public innovation programs

Abstract

Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. December 2016 Geographical Clustering and the Effectiveness of Public Innovation Programs AbstractThe paper analyzes how geographical clustering of beneficiaries might affect the effectiveness of public innovation support programs. The geographical proximity of firms operating in the same industry or field of technology is expected to facilitate innovation through knowledge spillovers and other localization advantages. Public innovation support programs may leverage these advantages by focusing on firms that operate in a cluster. We investigate this link using data from a large German program that co-funds R&D projects of SMEs in key technology areas called 'Innovative SMEs'. We employ three alternative cluster measures which capture industry, technology and knowledge dimensions of clusters. Regardless of the measure, firms located in a geographical cluster are more likely to participate in the program. Firms being part of a knowledge-based cluster significantly increases their chance of receiving public financial support. We find no effects, however, of geographical clustering on the program's effectiveness in terms of input or output additionality.JEL-Classification: C35, H50, O31, O32, O38, R59

Cluster role in industry 4.0 – a pilot study from Germany

“…These findings seem to be aligned with the recent literature conclusions, linking the cluster evolution with digital transformation and stressing the unabated cluster relevance to act as a useful policy tool (Grashof et al, 2019;Makers, 2018;Cantner et al, 2019). Though, the challenges inherent to adequate evaluation of cluster policy must be acknowledged and adequately addressed (Crass et al, 2019;Kiese, 2019).…”

The spinner innovation model: understanding the knowledge creation, knowledge transfer and innovation process in SMEs

“…SMEs constitute the majority of business firms, as well as the most significant source of employment, in any country worldwide (Manville et al , 2019). For such reason, policymakers frequently consider that SMEs perform a fundamental role in the technological progress of the broader economy (Thomä and Zimmermann, 2020) and therefore the greater their emphasis on knowledge, the greater their likelihood of gaining access to public financial support (Crass et al , 2019).…”

“…According to Thomä and Zimmermann (2020), policymakers frequently deem SMEs to perform only basic roles in the technological progress of an economy, and this significantly raises their chances of receiving public financial support whenever participating in knowledge-based clusters (Crass et al , 2019).…”

Innovation policy and public funding to stimulate innovation in knowledge intensive companies: the influence of human and social capital

“…For the intended purpose, the research addresses the literature gap, noting that the few existing papers usually assess generic impacts on the economy (Lerner, 2000; Wallsten, 2000; Lööf and Heshmati, 2005; Maula et al , 2007; Howell, 2017). Few studies take into account the level of effectiveness and the dimension of the technological evolution achieved (Crass et al , 2019), to propose indicators like the ones we use in this study, based on the scale of technological maturity (technology readiness level [TRL]). The TRL is largely used in the community of innovative companies and bodies that promote technological development and innovation.…”