Smart Specialisation (S3) is a place-based industrial strategy which forms the major component of the European Union's 2020 Innovation policy (RIS3). Lagging regions, however, lack the technological capabilities and networks to fully participate and benefit from RIS3. Extra-regional collaboration offers lagging regions opportunities for technological upgrading to overcome this deficit. Using patent data for EU NUTS2 regions, we find extra-regional collaboration raises innovation in lagging regions, although collaborations based upon technological relatedness might be less effective, compared to advanced regions. This has implications for the design of policies to engender extra-regional collaboration and their alignment with RIS3 initiatives.

This study acknowledges the diversity between micro, small, and medium‐sized firms while predicting bankruptcy and financial distress of the United States small and medium‐sized enterprises. Empirical findings suggest that survival (failure) probability increases (decreases) with increasing firm size and firms in different size categories have varying determinants of bankruptcy, whereas factors affecting their financial distress are mostly invariant. Magnitude of significant covariates changes across the size categories of both bankrupt and financially distressed firms. Further, operating cash flow information does not add any marginal increment in prediction performance of multivariate hazard models above baseline models developed using information from income statements and balance sheets. This result holds for failure likelihood of small and medium‐sized enterprises and their respective size categories.

At the heart of the European Union's innovation policy is Smart Specialisation Strategy (S3) as embodied in the Research and Innovation Strategies for Smart Specialisation (RIS3) programme. So far, RIS3's efficacy on the revival of so-called lagging regions has been weak. This is in large part due to the weak initial endowments of technology, social/business networks, poor governance and institutional failures that typify lagging regions. This combination inhibits both the effectiveness of the programme and the ability of lagging regions to take advantage of the new opportunities proffered by Industry 4.0. This paper highlights some of these challenges and presents some policy directions for S3 and Industry 4.0 to deliver better regional cohesion and enhance inclusive growth.

New technologies and sector imbalances due to manufacturing hollowing out have dented the regional stock of competencies in the EU labour markets. This raises concerns over the sustainability of the EU's competitiveness in the longer term. The present study sheds light on what occupational mix might be able to deliver greater regional productivity in the light of emerging industrial dynamics. We estimate panel regression models using regional data from the EU Labour Force Survey and Eurostat regional statistics. Our results show that regional gross value added is significantly improved if regions have a mix of occupations that includes what we define as smart workers: these are workers employed in advanced manufacturing and knowledge-based production-support activities. We also test interactions amongst production and production-support occupations as well as the non-linear effect between smart workers and regional gross value added. Policy implications are discussed. AcknowledgementsWe would like to thank three anonymous reviewers for detailed and highly constructive comments during the review process. Thanks to Raquel Ortega-Argilés and Stanley Siebert for helpful discussions on previous versions of this paper, as well as feedback from audiences at the

The purpose of this paper is twofold. First, to explore to what extent being located in a territory is value-relevant for a company. Second, to understand if a company is aware of, and how it can sustain, the territorial tangible and intangible assets present in the economic area in which it is located. Design/methodology/approach – The study presents an empirical multiple case-study, investigating ten mid-/large-sized Italian companies in manufacturing sectors.\ud The results indicate that the sampled manufacturing companies are intertwined with the environment in which they are embedded, both in their home country and in host ones. The domestic territorial capital has provided, and still provides, enterprises with workers endowed with the necessary technical skills that they can have great difficulty in finding in other places. In turn, companies support territorial capital generation through their activities

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Over the years, manufacturing in advanced economies has been the object of intense reorganization driven crucially by the international strategies of multinational enterprises (MNEs), and more recently, by technological disruptions powering a new manufacturing model, defined as Industry 4.0 (I4.0). This paper aims to explore firm-based, place-based and global drivers that can determine high levels of companies’ performance in the context of the emerging manufacturing model ‘I4.0’. In particular, our article tests the relative importance of and balance between three determinants of MNEs’ performance: (i) MNEs’ internal operations and R&D capabilities; (ii) reliance on local external economies and co-location with high-value service and technological competence; and (iii) the extent of MNEs’ production in terms of spread across global value chains. We empirically address this issue by surveying top managers of MNEs operating in four advanced manufacturing industries (biotech, engineering, fashion, and new materials) and located in five European countries (Germany, Italy, Spain, Sweden and the United Kingdom). We adopt fuzzy-set qualitative comparative analysis, a configurational, case-oriented approach. MNEs can be highly profitable when they follow different, but equally successful, paths. Our findings shed light on which balance between firm-based, place-based and global drivers positively impacts on companies’ performance in European advanced manufacturing sectors. In particular, we find that companies that collaborate with local suppliers of enabling technologies linked to I4.0 - with regard to the variety and intensity of collaborations- show high levels of performance. Policy implications are drawn in the concluding remarks.