As a response to globalisation of core manufacturing industries, and in particular their migration to emerging industrial countries in Asia, Western economic development policy has moved towards investment in specialised, high-added value technological products. Policy formulation focused on extending and exploiting geo-political and economic strengths and aimed to suport discrete industrial sectors, which can develop and retain global competitive advantage. In particular, variants of new industrial and innovation policy agenda (Radosevic 2017) have emerged as leading the way in this new agenda. These policy frameworks rejected both the principles of an absentee government in free-market economic deregulation of the turn of the twenty-first century as well as the doctrines of industrial planning of the post-Second-World-War era. The emerging policy compromise was in the middle of the said spectrumâgovernment-set priorities with free-market implementation. This gave rise to policymakers developing and deploying at-arms-length instruments and organisations in support of multi-party industrial developmentâin particular through innovation intermediaries.
Though many of the policy instruments are seen as ways of addressing perceived market failure (Arrow 1951) or government failure (Tullock et al. 2002), arguably policy can be more proactive in establishing economic opportunities where there has been none before (Mazzucato and Penna 2016). Perhaps the most well-known of such policy frameworks is the European Unionâs Smart Specialisation Strategy (S3 ) (European Commission 2014). S3 has by and large now been superseded by national innovation programmes and industrial strategies, however, under the surface these are actually very similar instruments. In an increasingly knowledge-based global economic system, these policies tend to focus on establishing and supporting industrial sectors with high productivity. High added-value products and services are particularly desirable as they increase countriesâ GDPs, as well as subsequent tax returns and develop global competitiveness. Hence, the policies strive to align the strengths of the scientific and technical knowledge base with the context of market formation using macro- and micro-economic instruments, supporting reindustrialisation (StojÄiÄ and Aralica 2018) and encouraging trade.
The critical underpinnings of such policies are, on the one hand, a rise in support for bottom-up development from start-up and spin-off companies and, on the other hand, an increase in openness innovation process as a guarantee of the competitive advantage on the global stage. A lot of the focus of economic and industrial development has thus shifted away from large corporations, sometimes labelled as ânational primesâ, and towards small- and medium-sized enterprises (SMEs). This corresponds to the increasing recognition of entrepreneurial and research and development (R&D) drivers for economic activities (Neffke et al. 2014; Wright et al. 2015). Knowledge-intensive technological entrepreneurship has been found to be particularly critical and a significant target for policymakers (Malerba et al. 2015; ThĂ©rin 2007). In particular, it is argued that a paradigm shift occurred through the conceptualisation of Open Innovation, that is the notion that innovation processes cross-organisational/firm boundaries (Chesbrough 2003).
The dynamics of Open Innovation is closely related to the innovation systems (IS) approach of understanding the consolidated capacity for innovation (Cooke 2001; Freeman 1991; Hekkert et al. 2007; Malerba 2002). Innovation systems analysis provides a comprehensive conceptualisation of the systemic nature of innovation, framed as an inter-organisational and context-dependent activity. The boundaries of such systems can be defined in different ways, though a combination of sectoral/technological and geographical considerations has been proposed as optimal (Edquist 2004). This has not always been taken up as consistently, and the innovation systems literature has split to examine either geographical (Cooke 2001; Nelson 1993) or sectoral/technological dynamics (Bergek et al. 2008; Breschi and Malerba 1997). However, a combined approach has been de-facto used in many studies, in particular in the field of innovation intermediation. This is likely due to geo-sectoral boundaries being helpful to study the complex landscape of innovation activities by stabilising the research within a relatively homogeneous environment of a shared knowledge base as well as exogenious factors (politics, economics, demographics, etc.). This framing can be acknowledged explicitly, by contextualising systemic innovation research as situated in Geographically-Bound Sectoral Systems of Innovation (GSSI ), as argued in this book and elsewhere (Vidmar et al. 2020).
However, there persists an acute lack of integration of the three key elements of understanding and supporting innovation: current micro-level literature on innovation process (Swann 2009); the meso-level literature on regional and sectoral innovation systems (Freeman 1991); and capacity building within the macro-level innovation policy context (Flanagan et al. 2011). In particular, this concerns the pathways linking micro-level organisational behaviours or firms and other actors, meso-level inter-organisational interaction between them and macro-level po...
