Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach

This study, utilizes an innovative methodological approach, fuzzy-set Qualitative Comparative Analysis (fsQCA), investigating the drivers of heterogeneous geographies characterizing English Local Economic Partnerships (LEPs). The fsQCA technique offers a novel configurational alternative to regression-based approaches investigating the effects of clustering in conjunction with firm-level innovation, university third-sector activity (TSA) and entrepreneurship, on LEPs innovation performance. The findings, offer contributions to the theories of industrial clusters and innovation, regional innovation systems, knowledge spillovers and entrepreneurial university innovation within LEPs. First, supporting fsQCAs, no individual variable generates either a positive/negative innovation outcome. Second, while all positive innovation recipes include presence of the cluster variable, for negative innovation recipes, only one does not identify absence of clustering as relevant. Given that the cluster variable does not appear in any recipes without at least one of the other variables suggests activity concentration does not exist in isolation to generate innovation outcomes without other localized conditions existing, e.g. firm-level innovation. Third, there is evidence for the non-cluster-based aspects of knowledge spillover theory of entrepreneurship with respect to university activity and the entrepreneurial university concept. Instead, roles of entrepreneurship and university TSA, while important, appear to be more peripheral and geographically context specific.