The European Commission has argued that while European research institutions are good at producing academic research outputs, they are not successful in transferring these outputs to the economy – the so called ‘European Paradox’ (European Commission, 2007). To improve competitiveness, an array of EU funded projects has been implemented across the 13 regions established for transnational cooperation and development activities. Nevertheless, there is a realisation that, “Too much of the research conducted in the region is not transformed into products and services for the market. There is still more to be done on building links between business and knowledge institutions and this is particularly urgent for SMEs, which often do not have the networks or capacities to access new research results” (The North Sea Region Programme Secretariat, 2013. p.5). Recognition exists that policies for the knowledge triangle are insufficiently joined-up, an example being the relatively minor role that the education and training dimension of higher education receives in policies for the European Research and Innovation Area (FarHorizon, 2010). There are various underlying structural problems concerning technology-transfer existing in Europe. A lack of coordination of policy instruments for research and innovation is causing problems within the enabling environment, which suggests that research must be carried out in order to measure the factors at play (Conti and Gaulé, 2009). Further research is also required to explore the internal organisation dynamics and external innovation ecosystem (IKTIMED, 2013), given university technology-transfer is underutilised in many National Innovation Systems.
Yet Etzkowitz noted as far back as 2004 that universities can contribute more towards economic and social development through third mission activities in the modern knowledge society. This agrees with Bercovitz and Feldman (2006) who concluded that an understanding of the evolution of the role of the university in systems of innovation certainly warrants further attention. They believe that if we are to think creatively about public policies towards increasing university technology-transfer, a focus on the larger innovation context is necessary. This also agrees with Marxt and Brunner’s (2013) findings that more research needs to take place to determine the measurability of higher education in relation to innovation at national level. Van Looy et al. (2011) found during their study that detailed studies are needed at university level to analyse the differences in strategic orientation, incentive arrangements and support structures (TTO), in order to determine the entrepreneurial practices deployed in universities (e.g. Debackere and Veugelers, 2005; Rothaermel et al., 2007). They also identified a gap in the documentation and analysis of the impact of (national or regional) innovation system characteristics in which universities are embedded, as an important complementary research endeavour. They contend that considerable opportunities for growth in the European Research Area is possible, on the basis that future research confirms the crucial role of national innovation system characteristics on the entrepreneurial performance of universities. In addition, during the course of their study, they noted a number of strong differences between European countries on the level of the entrepreneurial performance of universities, signifying the importance of further analysing these anomalies transnationally.
This is particularly interesting given Gunasekara (2006) highlighted the importance of understanding policy perspectives for university engagement at regional level, regarding the sustainable operation of universities. He suggests that there may well be heightened interest in how university engagement at a regional level can provide a basis for the sustainable operation of universities themselves. This suggests that there is a gap in knowledge regarding university transformation in relation to the regional system in which it functions. Nevertheless, Allinson (University Industry Innovation Network, 2013) succinctly pointed out that universities have to be many things to many people, and are facing a lot of challenges which require complex decisions. She highlighted that it is important for universities to protect and maintain their core mission, as this element needs to be strong for the future, as well as the need to protect fundamental research. This signifies the complexities universities face internally, through trying to balance core activities with those arising from interaction within innovation systems.
Drawing together the lessons learned from the literature, it is recognised that universities can play an important role in university technology-transfer activities within innovation systems. However, it seems that it is not easy for industry to collaborate with universities, and vice versa, given the variety of disciplinary orientations and missions of different
universities, and the differing aims and goals of industry. This means universities have to become more entrepreneurial through professional transformation in order to ease collaboration processes, and attract diversified sources of funding. Nevertheless, further research is required to explore organisational dynamics and bottlenecks, both internally within universities, and with external innovation ecosystem actors, in order to fully understand how the innovation system is influencing university transformation, and which bottlenecks are most restrictive towards transformation and output. This is certainly recognised as an important element to investigate to potentially enhance innovation systems, and understand how universities are responding to such changes, whilst also servicing their core missions.
The aim of this study is to understand how prevailing regional and national innovation systems affect university contribution, and transformation towards universities becoming more entrepreneurial.
The focus lies at the interface between universities and the innovation system. This should highlight the impact changes at regional and national level within innovation systems has on university contribution and transformation, thus pinpointing successes and challenges within the system; and secondly, determine similarities and differences through comparatively analysing these findings at regional level. The Life Sciences sector has been selected to narrow the focus.
The Main Research Question
How do prevailing National and Regional Innovation Systems affect university contribution, and transformation towards building an Entrepreneurial University?
Sub Research Questions
1. How and which actors of the innovation system have influenced universities to become more entrepreneurial?
2. What mechanisms (funding, platforms, programs, regulation etc.) exist in the NIS / RIS to harness university contribution to innovation and economic development?
3. What are the organisational barriers and enablers for university engagement to become more entrepreneurial?
4. How do actors and mechanisms of the innovation system ease contribution processes by universities?
Literature pertaining to the phenomena under investigation was examined to analyse the main theories and concepts relating to the overarching themes: Innovation Systems, and the evolution of the Entrepreneurial University. As such National and Regional Innovation Systems, Triple Helix Theory and issues relating to university transformation were explored.
The concept of the National Innovation System (NIS) was originally developed by Freeman (1987), Lundvall (1992) and Nelson (1993), whereby the overall notion was defined to describe the interaction of elements and relationships to produce and diffuse knowledge which is economically useful within a country’s borders (Lundvall, 1992). It is clear that much of the work carried out pertaining to the NIS was targeted to small countries such as Sweden ,Norway, Denmark, Finland, Japan, and Cyprus for example, which is evident in various author’s work (e.g. Lundvall et al., 2011; Kapetaniou and Lee, 2013). Interestingly, Lundvall et al. (2011) found that these small countries prosper because they have a highly developed capacity to absorb and use new technology used elsewhere - something they have in common with developing countries. The literature to date can be split into two categories, encompassing a narrow or broad approach. The narrow approach focuses on institutions and policies directly involved in innovation
such as the STI policies (Science, Technology and Innovation) (OECD, 1999). Whereas the broad approach takes into account the social, cultural and political environment (institutional system / framework) of the country context. This includes a nation’s financial system; its monetary policies; the internal organisation of private firms; the pre-university educational system; labour markets; and regulatory policies and institutions; as well as the aforementioned narrow components (Feinson, 2003).
Fagerberg and Sapprasert (2011) highlight that literature regarding the systems approach towards innovation has grown rapidly since 2003, across a range of disciplinary areas. What is clear is that such systems must respond to needs, thus the coupling of mechanisms and policies is a bid to achieve a well-functioning NIS which delivers upon the technological and social innovation needs of a nation (Godin, 2010). Lundvall et al. (2011) point out that old style hierarchical modes of organising work may increasingly become barriers for the kind of intra-organisational interaction that is necessary to become a lead innovator. Lundvall (2005) noted that some of the conceptual openness of the concept of a NIS refers to the fact that historical and local context affects where the limits of innovation systems are set. These findings highlight the importance of fully understanding the historical context and existing framework of a NIS, when designing and implementing changes within the system. It is clear that innovation processes are evolutionary and path dependant (Johnson, Edquist, & Lundvall, 2003), meaning you cannot easily transplant a ‘high performance element’ from one system to another and expect similar results (Lundvall, 2005). Lundvall (2005) noted that the NIS highlights importance of interaction with universities on the innovative capabilities of SMEs, which is important for innovation and regional and economic development. Yet gaps exist in understanding how the formation and openness of the NIS affects how universities interact, and indeed contribute towards economic development within the system. Lundvall (2005) posits that more research is needed to understand the openness of national systems, and the relationships that exist within this dynamic, particularly given the varying role governments’ play in economic development.
Given the regional focus of this particular study, it is apt to consider innovation systems from a regional perspective. Johnson, Edquist and Lundvall (2003) note that systems of innovation can be delimited in a number of ways: spatially, geographically, sectorally, or according to the particular activities they focus upon. As such, systems of innovation with a geographical emphasis can be considered at the local level, regionally, nationally, or at supranational level. it is important to consider the RIS within the frame of the prevailing NIS given the institutional elements of the RIS are largely shaped by the overarching national system; as such, their organisational structure, funding, and activities are dependent on national level policies and public resources (Doloreux, 2002). Governments, particularly those situated within advanced economies, realise the potential of regional innovation systems. As such, clustering policies and regional innovation have been promoted as a means to boost national competitiveness (Cook and Memedovic, 2003).
Universities’ role within RIS has evolved considerably over the last 20 years, given the extension towards partaking in ‘third mission’ activities has transformed how universities function internally, but has also transformed how they are perceived within innovation systems (Gunasekara, 2006). By way of a comparative university case study, Gunasekara (2006) noted the importance of understanding the policy perspective for university engagement at regional level, with particular regard to the sustainable operation of universities. He argues that the distinctions highlighted through the Triple Helix model and university engagement literatures are material, given the need for real evidence to inform policy as to how university engagement at regional level can provide an appropriate basis for the sustainable operation of universities themselves. This statement highlights the need to bridge existing theories regarding these phenomena with real life situations, thus compounding the need for the current research endeavour. Interestingly, Gunesekara (2006) noted that a combination of institutional and economic factors determine the role universities perform in the development of a RIS. Despite this, the general university engagement approach (which emphasises universities contribution towards the economic and social development of a region) plays down the differences in university missions; path dependent evolution and positioning within a region; and also oversimplifies the willingness and indeed capacity of universities to adapt their functions in response to external signals (Gunesekara, 2006). What’s more, Asheim and Coenen (2005a) identified that analysis of different types of RIS must take place within the given context of the knowledge base at industry level, given a range of industry sectors may be present.
Triple Helix theory, developed by Etzkowitz and Leydesdroff (1995) explores the relationship between university-industry-government as sub-dynamics within innovation systems. It is imperative to understand the complexity of each node, given government can be considered at local, national, regional or supra-national level (Marginson and Rhoades, 2002); industry can be classified into different sectors and type of business (Metcalfe, 2010); and universities can be further classified by various sub-dimensions such as public or private control, size, geographic location, and institutional ranking, to name a few (Metcalfe, 2010). Therefore, the Tripe Helix thesis can be considered as widely applicable, yet it can also enable a narrow focus on specific elements within an innovation system through appropriate selection and analysis. The Triple Helix explores the ‘systemness’ of an innovation system and thus benefits from the confines of geography to delimit particular empirical case studies under investigation (Leydesdorff, 2012; Leydesdorff and Zawdie, 2010). It highlights the potential for innovation and economic development through the generation of new institutional and social formats for the production, transfer and application of knowledge (Ranga and Etzkowitz, 2013). It focuses on innovation systems at various levels in terms of institutional and functional categories, which can potentially contribute towards the improvement of the effectiveness of innovation policies at regional and national levels (Leydesdorff and Zawdie, 2010). Etzkowitz (2002) defines the first dimension of the triple helix model as the internal transformation within each of the helices, in the case of the university this could constitute the progression towards an economic development mission. He states that the second dimension pertains to how one helix influences another. Lastly, he contends that the third dimension deals with the creation of a new overlay of trilateral networks and organisations, which evolves from the interaction between the three helices. Therefore, this creates a spiral model of innovation, which acts to capture multiple reciprocal relationships at various points throughout the process of the capitalisation of knowledge.
Nevertheless, Leydesdorff (2012) argues that the definition of a system is no longer what it used to be, and remains in transition given dynamics relating to local, regional and supranational environments and actors. In addition, he contends that when more than two helices are in operation, this opens the possibility for chaotic behaviour, which requires stabilisation along a trajectory, with government tending to provide this stabilisation through ongoing interactions, and perhaps domination in some contexts. Nevertheless, Leydesdorff (2012) also points out that dynamics within individual nodes are two fold, given that although nodes develop upon their internal axis (i.e. their own primary paths), they will inevitably be affected by external developments which impact the functionality of interaction and communication. In addition, they are also constrained by their own specific institutional settings, functions and culture. This highlights why it is so important to understand transformation within universities in relation to their prevailing innovation systems.
Throughout TH theory’s development, differing perspectives have been explored including the (neo) institutional perspective, the (neo) evolutionary perspective, from the perspective of the Entrepreneurial University, and through the concept of Triple Helix Systems of Innovation (Stanford University, 2014). Regarding the current study, the (neo) institutional perspective and perspective of the Entrepreneurial University are most relevant for further exploration. The (neo) institutional perspective examines the growing prominence of the university among innovation actors through national and regional case studies, which reflects the current methodology employed in this study. In addition, this particular perspective focuses on various aspects of the university ‘third mission’ of commercialisation of academic research and involvement in socio-economic development (Stanford University, 2014). As such, it takes into account the variety of stakeholders, drivers and barriers, benefits and impact, university technology transfer and entrepreneurship, contribution to regional development, government policies aimed to strengthen university-industry links, and so on. (Stanford University, 2014). Importantly, it differentiates between three main configurations in the positioning of government, industry and university in relation to each other, including the statist configuration, the laissez-faire configuration, and the balanced configuration; whereby the intersection of these three spheres in this balanced configuration is perceived to provide the most favourable environment for innovation (Etzkowitz and Leydesdorff, 2000).These configurations highlight the dominance of State control in the statist model, the disconnection between individual spheres in the laissez-faire model, and the favourable overlap between spheres in the balanced Triple-Helix model. This overlap is particularly important, given the development of trilateral networks and hybrid organisations which have developed in order to enhance interactions between and among spheres. This is of course essential to produce, accumulate, and diffuse knowledge for promoting competitiveness through innovations (Lundvall and Johnson, 1994; Archibugi and Lundvall, 2001).
Of particular relevance, is the concept of the Entrepreneurial University, which is a central concept within the Triple Helix model. Academia’s role in creating and applying new knowledge through ‘third mission’ activities is a salient feature of the Entrepreneurial University. This is because socio-economic development is a fundamental outcome associated with its activities and role within the Triple Helix, particularly given intellectual assets are considered renewable and thus a strong source for continued regional development (Etzkowitz and Dzisah, 2008). As such, the economic impact of universities through R&D effort to GDP is noteworthy (Farinha and Ferreira, 2013), however, Kapetaniou and Lee (2013) and Hazelkorn (2006) argues that a university needs to be directly linked to the industry in order to maximise the industrialisation of knowledge. A number of authors have argued the importance of these three institutional spheres (university – industry – government) as fundamental components to enhancing regional and national innovation systems (Etzkowitz, 2003a; Etzkowitz, 2003b; Etzkowitz and Leydesdorff, 2000; Leydesdorff and Meyer, 2006; Cooke and Leydesdorff, 2006; Smith and Bagchi-Sen, 2010; Etzkowitz and Dzisah, 2008; Huahai et al., 2011; Galindo et al., 2011). Importantly, it is recognised that universities may indeed perform an elevated role in innovation within the context of knowledge based societies (Etzkowitz, 2003a; Etzkowitz, 2003b; Leydesdorff and Meyer, 2006; Etzkowitz and Dzisah, 2008; Etzkowitz and Leydesdorff, 2000). This is especially true as nations aim to move from industrial economies to knowledge based economies. Further, the formation of collaborative links between innovation actors is a central concept of the Triple Helix model, and universities have found themselves at the centre of such developments through their valuable production of scientific research. Nevertheless, one problem of the Triple Helix model is its focus on a top-down system level, rather than on the peculiarities of individual actors (Leydesdorff and Zawdie, 2010). This is pertinent given no two universities are the same, or indeed follow any typical path towards becoming entrepreneurial. Therefore, this highlights the need to better understand the impact of interaction on university transformation.
The availability of funding has changed dramatically over the past decades, with reductions in national public funding allocations for universities. There has been an orientation towards linking HE policies with economic innovation strategies (Hoareau, Ritzen and Marconi, 2012), and designing funding mechanisms to increase economic activity. This is likely due to the recognition that universities’ are perceived as potentially key actors in processes of entrepreneurial discovery which lies at the centre of smart specialisation processes (ESMU, 2012). As a result, growing political pressure is present for universities to increase their own research funding options through intensifying interaction with industry, given level of competitiveness is likely to be impacted if reducing public funds are not matched by private sources (Muscio, Quaglione and Vallanti, 2013; Hoareau, Ritzen and Marconi, 2012). Koryakina, Teixeira and Sarrico (2012) also noted the importance of income diversification in European universities given the deficit in funding resulting from shortages in public finances. They note that governments have tested different approaches as a means to attract finance to higher education systems, through providing tools for revenue diversification, and also through the introduction of market mechanisms. In addition, Koryakina, Teixeira and Sarrico (2012) argue that this diversification of income is a potential source to improve the current deficit in innovation, through promoting knowledge transfer within public-private partnerships. Nevertheless, the introduction of market mechanisms has created a more business like environment, given universities now have to compete for research funding and attract tuition fees. As a result, how universities are run is transforming in response to such measures, as outlined by Clark (1998). He notes this business-like behaviour in the way universities are changing structurally and also managerially, and uses terminology borrowed from the business world to describe the types of strategic thinking, committed leadership, institutional governance, entrepreneurial culture, and flexible and responsive organisational structure, to illustrate this evolutionary pattern (Clark, 1998). Work by Bercovitz and Feldman (2006) on university-industry links emphasises universities’ role in regional systems of innovation as the primary driver of economic development. This ideology agrees with Palmintera (2005), who believes there is no doubt that university technology-transfer and commercialisation activities are impacting local, state, and national economies. As Bercovitz and Feldman (2006) conclude, an understanding of the evolution of the role of the university in systems of innovation certainly warrants further attention. They believe that if we are to think creatively about public policies towards increasing university technology-transfer, a focus on the larger innovation context is necessary. This also agrees with Marxt and Brunner’s (2013) findings that more research needs to take place to determine the measurability of higher education in relation to innovation at national level.
Overall, universities recognise the increasing need to supplement their funds to carry out their multiple missions, with results from Koryakina, Teixeira and Sarrico’s (2012) Portuguese case study highlighting that revenue diversification activities were recognised as drivers of institutional dynamics and development. This shows the enormous impact regarding how available funding streams within innovation systems have the power to create transformational change within universities. Clark (1998) found, an entrepreneurial university can be analysed from five dimensions; namely, strengthened steering core (whereby universities need greater organisation internally in order to become quicker and more flexible in their ability to adapt to changing demands in the wider environment); diversified funding base (whereby universities need to increase financial resources through expansion of possible third stream funding sources); expanded development periphery (whereby universities need to create appropriate infrastructure in order to forge links with outside organisations more easily and professionally); stimulated academic heartland (whereby measures must be taken to stimulate university staff, particularly academics to embrace and carry out change for ultimate transformation); and entrepreneurial culture (whereby universities must develop an institutional culture over time that embraces change, in order for it to become rooted in practice, and become a shared value amongst staff). It seems that a university not only requires structural change in the first three dimensions, but also requires buy-in at the cultural level described by the remaining two dimensions, especially given universities are people oriented institutions, whereby people are the driving force to enact change. Interestingly, Kivisto (2007, p.194) noted during his study that in general terms, the government-university relationship seems to contain the essential conditions that should be present in an agency relationship: namely informational asymmetries and goal conflicts. This illustrates the difficult relationship between government and universities by highlighting issues of transparency which lead to issues of mistrust, and also the differences in end goals which persist between these two actors. Literature pertaining to academic capitalism discusses to great length the differences in orientation of academics to pursue third mission activities (Slaughter and Leslie, 1997). There is a tendency in some settings for individual academics to pursue such commercial activities, with strong resistance from the majority of the collegial body to such developments (particularly in the more traditional universities). In other cases, entrepreneurial spirit appears to be more embedded in the organisational culture, with modern universities displaying this type of entrepreneurial drive.
Organisational structure plays an important role in the successes of entrepreneurialism. Considering that adhocracy and market quadrants dominate in entrepreneurial universities, flexible organisational structures are required for responding to the external environment more quickly, which is particularly important given the competitive nature of this environment. Therefore, universities must be strategic and adaptable to change (Spanier, 2010), and the easiest way to aid change is through the hierarchy and organisational structure in place. Glaser (2012) argues that the internal and external governance structures of the university have shifted and become more entrepreneurial, meaning the relationship between the ministry and the universities shifts to vertical steering structures based on negotiated objectives and performance contracts. Nevertheless, Martinelli, Meyer and von Tunzelmann (2008) argue that differences in motives and organisational structure can lead to conflicts due to cultural differentiations in how administrators and academics carry out their activities, with the former too aggressive in bargaining, or acting in an excessively bureaucratic fashion. In addition, Martinelli, Meyer and von Tunzelmann (2008) found that individual characteristics and perceptions about potential risks of external links for scientific values may explain the personal propensity to different types of entrepreneurship better than university policies and organisation.
This qualitative study has been designed as a case study, given this method is designed to focus on a specific problem, in order to determine the characteristics of the selected case within a bounded system, through utilisation of multiple sources of data (Ary et al., 2010). Based on Yin (2009), Bray, Adamson and Mason (2007) and Creswell.
(2007), this case study is designed as an empirical enquiry. It utilises a pragmatic yet holistic approach, to investigate this phenomenon in-depth within its real life context, through abductive reasoning. This collective case study explores two bounded systems (the regions of Vienna and Stockholm), thus enabling an in-depth analysis to take place (Creswell, 1998; Ary et al, 2010). Predominantly qualitative primary and secondary data will be utilised, given the study is heavily context based. The limited focus of this study is designed specifically to cope with the numerous variables which are likely to present themselves, given data is designed to be obtained from multiple sources. Nevertheless, multiple source data will be useful for triangulation purposes. This study will benefit greatly from the prior development of theoretical propositions to guide data collection and analysis (Yin, 2009). Focusing on Level 2 of Bray and Thomas’s (1995 as cited in Bray, Adamson and Mason, 2007) Cube, emphasis is placed primarily at regional level, with a broader focus to capture the prevailing context of the national innovation system, given this has a strong bearing on what takes place at regional level. Perspectives from the concepts of National Innovation Systems (Lundvall, 1992), Triple Helix (Etzkowitz, 2002), and Entrepreneurial Universities (Clark, 1998) have played an important role for the formation of the analytical framework and consequently, the formulation of interview questions and data analysis, which will be discussed shortly. A comparative approach has been utilised to study the problem through a combination of two theoretical lenses, in order to deduce explanations of relationships identified, and thus provide insights to the problem.
Given the unique focal point of the study, elements from three concepts has been utilised to design a frame of analysis specifically for this study. As such, Lundvall’s (1992) National Innovation Systems, Cooke, Uranga and Etxebarria’s (1997) Regional Innovation Systems, Etzkowitz and Lededorff’s (2000) Triple Helix, Metcalfe’s (2010) focus on Tri-lateral relationships within the Triple Helix, and Clark’s (1998) Elements of Entrepreneurial University Transformation have been adopted. First, the research question has been framed by considering how the university fits within the National Innovation System, this has helped to identify the focal point of the research at the interface between university and the external innovation system. Secondly, the actors, relations, and mechanisms have been considered based upon Triple Helix principles, to design the sub-research questions, and ensure the study maintains questions which relate to the innovation system, and connect to the specific actors under study. Finally, three main dimensions from Clark (1998) (Strengthened Steering Core; Diversified Funding Base; and Entrepreneurial Development Periphery) have been adopted specifically to design questions which probe university transformation in relation to prevailing innovation systems. Nevertheless, the remaining two dimensions of Clark (1998) (Stimulated Academic Heartland; and Entrepreneurial Culture) have been considered in conjunction with these elements given transformation lies with the actors who carry out the change, and consequently, these dimensions have an impact. However, given studies already exist exploring this particular phenomenon, this element has taken a minor role in the current research endeavour. The Analytical Framework is shown in Table 1:
Table 1 Analytical Framework (Source: Own depictio).
Multiple sources of evidence were utilised, with a case study database created to hold and organise all literature, data, raw data, and analysis, as the project progresses. Unique case sampling was the favoured method in order to select specific universities involved in the life sciences sector, to maintain a narrow focus. In this instance, 4 universities and 8 innovation system actors have been selected from 2 regions identified as areas where the Life Science sector is of economic importance. This particular selection is based on the need to interview expert trilateral actors as reflected within the Triple Helix literature of the importance of trilateral relationships for stimulating interaction (Metcalfe, 2010). University actors were selected on the basis of ensuring representation from different levels within the university (i.e. management, technology-transfer office, and researchers) in order to understand the impact and implementation of transformation processes at different levels within the university. In addition, the semi structured interview approach was adopted as the primary data capture method, given it enables flexibility to follow interesting paths as they arise, is advantageous as it supplies large volumes of in-depth data, and provides deep insights into that particular person’s perspective on the situation. The aim was to target between 20-24 interviewees, with a minimum of 15-20 considered an acceptable lower limit. In the end, 17 interviews were obtained. Questions were piloted and amended before use to ensure reliability, and interview guides compiled to address targeted data collection from the variety of actors involved. As such, comparable questions were constructed according to the adopted criteria within the analytical framework to address each indicator. Secondary data sources were identified to gather information relating to the national and regional innovation system. National sources (e.g. BMWFW, Vinnova) and supra-national sources (e.g. EU, OECD) have helped to give an overview of the prevailing innovation system in which the case studies are located. In addition, it was noted that indicators used in secondary data can give a limited view. As such, definitions and supplementary qualitative analysis helped overcome any potential erroneous traps.
Each semi-structured interview was recorded for accuracy of transcription, and subsequently coded and tabulated to enable comparisons internally, regionally, and trans-nationally. Checks were made systematically, to ensure avoidance of misinformation, or mistakes during data collection and analysis. After data was coded, and organised, themes were selected based upon the analytical framework (outlined above). Data analysis took place to first search for significant patterns in the data, and then individually address the selected indicators and ultimately answer the research questions. This enabled a theory to be constructed as the investigation progressed. To promote credibility of the project, evidence is based upon structural corroboration through the selection of several representatives per university; several representatives from the innovation system; and utilisation of secondary data relating to the universities and innovation system. This has enabled triangulation of data. Regarding transferability, it is feared that generalisations of the results cannot be readily applied to all universities within the countries under review, given the sample size is too small. Nevertheless, as cross-case comparisons are being utilised as the core element of this research endeavour, it may be possible to generalise to a small extent, but one must bear in mind the selection effects of the adopted narrow focus on the Life Science subject area. In addition, the results are also contextual, given the regional focus of the study, again affecting transferability of the results.
After investigation, it appears that prevailing innovation systems and their overarching institutional frameworks affect the level of university contribution. This echoes and extends Hoareau, Ritzen and Marconi’s (2012) finding that political systems may influence performance of their public policies. Interestingly, the regional dimension of innovation did not have as much impact as the overarching national dimension. This is due to the fact that many mechanisms and policies are rolled out at national level. Nevertheless, it was clear that the regional dimension came into effect
concerning actors and small proportions of regional funding which are targeted towards the Life Sciences sector. This reflects findings by Davey et al. (2009) who found that regional strategies play to key strengths of a region. Yet in the Swedish case, it was clear that the national system prevailed, with only regional competition being highlighted as a detrimental factor to development. However in the Austrian case, it seemed that regional dynamics played a stronger role, as Federal States seem autonomous in their activities, and very much disconnected. This disconnection also echoed in the governance of the innovation system, with knowledge triangulation policies still quite disconnected in their orientation (European Commission, Erawatch, 2014a). The structure of the system definitely echoes the principles of the National System of Innovation (Lundvall, 1992). Nevertheless, the system seems quite hierarchical and disconnected, and could potentially learn from Sweden in this case, given Lundvall et al. (2011) pointed out that intra-organisational interaction is necessary, as hierarchical modes of organising can create barriers. As such, the Triple Helix approach prevails in Sweden, which is possibly aided by the flat structure present in the country, as well as the types of funding programmes and various mechanisms in place to stimulate collaboration between different nodes. This reflects Lundvall’s (2005) finding that historical and local contexts affect the extent to which innovation will take place. Therefore, focusing on the system dimension, rather than solely on STI policy creates greater connections which are contextually relevant to the case country’s economic, political, and cultural traditions (Lundvall, 2005; Ramstad, 2009). However, much work still has to be done given closer inspection revealed that transfer of funding between sectors does not take place to a large extent (European Commission, Erawatch, 2014b). This particular anomaly requires further analysis to determine why.
In both country cases, government (or its associated agencies in Swedish case), appear to have a fundamental impact on how universities are transforming. This can be attributed to policy changes (in the Austrian case) whereby further autonomy has been granted to universities as a means to enable them to professionalise and secure diversified sources of funding from elsewhere in the innovation system. It can also be attributed to various short-, mid-, and long-term funding projects (in both country cases), whereby universities are being steered towards priority thematic areas, and to also collaborate with other actors in the innovation system, given the rules and regulations of acquiring such funding. Nevertheless, the disciplinary focus and traditional orientation of each university case reflected its level of entrepreneurial activities and transformation. Both BOKU and KTH Royal Institute of Technology have had close links with industry for several decades, and this reflected in the structural and organisational transformation that has taken place over time, and the generally positive attitudes of academics towards contributing to the innovation system. Therefore, although bridging organisations are vital to connect actors, and industry are incredibly important in collaborating with universities, it seems government plays a pivotal role in creating the appropriate entrepreneurial innovation environment whereby universities have enough autonomy and resources to contribute efficiently, whilst also maintaining their core missions.
In particular, the University Act 2002 and uni:invent programme have played pivotal roles in the Austrian system for the entrepreneurial transformation of universities. Although Swedish universities feel restricted in their autonomy, they have also benefited from targeted funding for the development of Innovation Offices. This particular infrastructural development has been a positive development to bridge university commercialisation in the innovation system. Competence Centres have also been highlighted in both cases as being pivotal, considering the unique innovation environment and platform it provides. Its long-term orientation also enables trust building, which has been noted as a fundamental element in university collaboration processes. In addition, government funding programmes in both country cases has been noted as being particularly important in order to increase funding allocations to universities. Nevertheless, government need to provide more risk capital to bridge the gap created by the low number of venture capitalists, given current institutional frameworks and prevailing cultures are still in their infancy in this regard in both country cases. From the university perspective, having support from university management, and inclusion of entrepreneurial activities within strategy documents and development plans of a university, seems to promote successful transformation, given entrepreneurialism permeates throughout the system as a result. Other important mechanisms such as IP policies and the Teacher’s Exemption have also highlighted that elements from these mechanisms could potentially be adopted into systems to ensure transparent collaboration, and also incentivise academics to collaborate.
Nevertheless, a number of barriers were highlighted which were common to both innovation systems under analysis. A lack of funding was the main barrier, highlighting that targeted funding could reduce current bottlenecks in the system. Areas requiring attention include the need for higher levels of basic university funding from government, in order for universities to be able to match fund industry projects and maintain their independence in such collaborations. Higher allocations of risk capital is also missing within the system, requiring government to bridge the current ‘Valley of Death’. In addition, further funding is required to improve and increase infrastructure within universities, and enable the recruitment of further human resources for TTOs, given the current situation is limiting its collaboration volume potential, thus capping its income potential. This reflects Koryakina, Teixeira, and Sarrico (2012) who noted that there is a need for appropriate infrastructure to support emerging third mission activities. From a structural and organisational perspective, external innovation actors noted difficulties relating to the variety of university structures present, thus requiring varying individual approaches. Further, the vast number of people external innovation actors need to know within universities also increases the time taken to form collaborations, which adds complexity to creating collaborations. In addition, bottlenecks exist regarding knowledge transfer internally within universities and what is made available externally to innovation actors. This requires the design and utilisation of knowledge management systems in order to avoid duplication of research, enable greater transparency of projects, and create efficiencies in the distribution and development of knowledge for commercialisation. However, it seems tensions exist within universities between operating a professional business model and performing the core traditional functions of the university, which stems from limitations in time, funding, and in some cases, academic cultures present within universities, and their subsequent resulting engagement in commercialisation activities. Care must be taken to overcome this hurdle, given conflict between academics and administrators within universities can inhibit transformation and development (Martinelli, Meyer and von Tunzelmann (2008). Culture plays an incredibly important role within such processes, both within universities and in the broader innovation system, and it was found that differing cultures between nodes also created tensions during collaboration. Therefore, this requires a balanced approach, taking into account structural, organisational, and cultural bottlenecks simultaneously.
It is also important to align these barriers identified at the micro level, with those highlighted at the macro level. In the Austrian case, the prevailing bureaucratic structure, and perceived lack of a clear strategy and goals, and indeed varying goals and strategies between actors, was considered a major inhibitor for development within the system. In the case of the Life Sciences sector, the complicated situation regarding the healthcare system was also identified as an inhibitor. Despite its proximity to universities, its governance structure currently creates a major barrier for the uptake of innovations flowing from universities and the innovation system. However, this particular issue goes beyond the scope of the project. In the Swedish case, it was clear that a differing governance system was in place, with much more control afforded to the associated agencies. However, the legal system was perceived as a barrier given rules and regulations associated with basic university funding. Despite this, the Swedish respondents felt happier with the level of basic funding received. Nevertheless, both country case representatives noted that the academic emphasis on producing publications rather than number of commercialisations has great impact on output, reflecting similar tensions found by Martinelli, Meyer, and von Tunzelmann (2008). This can be attributed to the traditional tenure system in place, which also impacts the mobility of researchers between industry and academia, particularly later in their careers. Therefore, this requires attention at system level, in order to create balance and overcome issues between public and private knowledge. Returning to the issues of culture, it appears that a culture for innovation and entrepreneurialism prevails in Sweden, which could indicate why, despite their identified bottlenecks, they are still categorised as an Innovation Leader. It would be interesting to delve further into their differing governance structure, to understand how applicable this system may be in other country cases such as Austria.
A number of enablers were also identified in both country cases, with Competence Centres identified as an excellent long-term initiative, providing a much needed platform where trust building could take place. In addition, expanding the development periphery of universities through the addition of TTOs has also been hailed as a successful development for easing the collaboration and contribution processes of universities within the innovation system. This is likely due to the professionalisation of the system, and the increased visibility of this interface, whereby external actors can interact and collaborate more easily. However, it should be noted that presence of the TTO alone is not enough, and requires a commitment from leadership, and appropriate processes, functions, and IP policies in order for it to be successful. Elements of the Teacher’s Exemption, a highly debated issue within the study, could potentially yield good results if
adopted carefully within a university system. Pressures on academics and their general orientation towards the core missions of teaching and research, tends to reduce the efforts directed towards commercialisation. Nevertheless, balance is required when considering to incentivise commercialisation, given its potential detrimental impact on these aforementioned core functions. As such, additional human resources could potentially alleviate such burdens, and thus requires complex strategic solutions to overcome this issue.
It appears that all actors play a role in easing university contribution to the innovation system, however government plays an elevated role due to developments in national and EU strategy documents, their allocation of funding through various mechanisms, and changes made to legislation (e.g. University Act 2002 in Austria). Targeted funding towards the development of TTOs in both cases has enabled universities to professionalise their organisation and functions in response to the innovation system. The most successful transformation cases included those where entrepreneurial activities were embedded within the mission and the strategy of the university, and considered as day-to-day activities. Therefore, this incorporates the same importance placed on the other core missions of the university, echoing the University of Waterloo’s approach towards promoting entrepreneurialism throughout its vision and mission statements, as a means to serve as an institutional enabler of entrepreneurial culture within their institution (Bramwell and Wolfe, 2008). Nevertheless, the traditional orientation of the university plays a strong bearing on how well it can interact and contribute to the innovation system, with the Life Sciences area considered a strength in this respect. It was also noted that the formation of broader schools within universities went some way towards creating conducive environments for collaborative activity. Nevertheless, the creation of unstructured platforms through internal clustering seemed to be a successful addition in the aim towards creating cross-disciplinary environments- an area many respondents felt was underdeveloped and underutilised. However, due to the lack of funding available within the system, universities have to take strategic decisions regarding which IP is pursued, and as such identification of niche markets has been a pivotal strategy to deal with lack of funding, but place focus on key strengths of universities. Therefore, it is apparent that it is not only actors and mechanisms in the system that eases university contribution, but also universities themselves through transformation and professionalisation. However, successful transformation needs incremental change over a considerable period of time (Clark, 1998), which appears evident, particularly in the case of BOKU and KTH Institute of Technology. In addition, a mixture of structured and unstructured transformations appears to be conducive to the entrepreneurial development of universities, and subsequently, their contribution potential. This could be due to the fact that structured transformation provides a visual organised and professional model which is clearly understood by external actors, and can be managed in terms of day-to-day functions, and financial health. Whereas the unstructured approach to platforms and academic networks utilises the flexibility, freedom, and individual characteristics of research disciplines and the people carrying out the work. Therefore, this highlights the symbiotic nature of solutions required between universities and external actors to increase growth of the innovation system, through creation of a dual structure. Nevertheless, given the high complexity present, simplification is imperative to ease collaboration processes through reducing bureaucracy, and attempting to control chaotic behaviour that can take place when two or more nodes collaborate. This could be further eased through reducing competition in the system and increasing collaboration to create efficiencies.
From a comparative perspective, the life sciences are a very important sector economically in both the Stockholm and Vienna regions. Governmental strategies in both regions pay attention to this area; however, Sweden has taken a stronger long-term strategic approach to development through directing large public investment towards the sector and its infrastructure. Nevertheless, Austria is not far behind in its approaches, however strategizing and investment is more conservative in this case. The comparative analysis of the case universities highlights that all universities are becoming increasingly professionalised and entrepreneurial, although this is taking place at differing levels and time scales. The medical universities appear to be more traditional in culture and structure, particularly in the Swedish case. However, this is changing, as pockets of academic entrepreneurs are increasingly participating in collaborations and technology-transfer activities. Nevertheless, it was highly noticeable that both KTH Royal Institute of Technology and BOKU are much more entrepreneurial, and also have a longer history of development in this respect. Additionally, a culture for entrepreneurial activities was strong in both institutions. This may be attributed to the fact that entrepreneurialism was given greater emphasis within the mission and strategy of these universities in comparison to the medical universities, with buy-in from top management clearly evident in the long-term planning for collaborations, particularly in the case of KTH Royal Institute of Technology. Overall, it appears similar barriers exist for universities in both regions, which suggests that these are national system level anomalies. Therefore, there is a need for structural easing, particularly regarding autonomy in the Swedish system. Additional funds are also required, particularly in the Austrian system, in order to give universities more flexibility and power, and also bridge current funding gaps.
Comparing national and regional innovation systems, the national system predominates in both country cases; however, some regional differences occur, particularly in Austria, where federal regions appear quite autonomous in their strategies and approaches. In this case, Austria has afforded more autonomy to its university system in comparison to Sweden, which has enabled universities to take more decisions, and professionalise accordingly. This particular move would be beneficial in the Swedish system to increase the scale at which universities can make decisions regarding infrastructure and the financing of technology-transfer activities. Interestingly, the governance structure in Sweden is quite different to that in Austria, with governmental agencies having greater power and autonomy to interpret strategies and distribute funding. Despite disconnections, fragmentation and disjointed structural problems in each case country, the clarity and focus of innovation strategies appears stronger in Sweden. Nevertheless, both regions, and indeed countries, face similar issues, including the gap in funding known as the “Valley of Death”, which is ultimately causing a gap in innovations within the system. Weak links also exist between academia and industry generally, despite some universities having elevated success in this area. It will be interesting to track the progress of the current large targeted financial investment in Sweden, especially given governments there have identified the importance of investing in infrastructure and research in a centralised way in order to get more out of capital expenditure in research and development. As such, timing of investments and targeting towards pivotal areas seems to have been what has led to greater success in the Swedish case, given investment in the life sciences, for example, has been identified as an area for building long-term competitiveness. The development of incubators clusters and bridging organisations seems strong in Sweden, although Austria is also making good progress in this respect, with various Centres of Excellence and bridging organisations such as LISA Vienna easing collaboration processes.
Following Triple Helix theory, it seems governments are aware of the importance of connecting the dots between academia, industry and government; however existing National Innovation Systems and their prevailing institutional frameworks dictate the complexities of enabling these connections to be made. This highlights the need to consider how prevailing governing structures and legislative frameworks are impacting innovation system dynamics. This is particularly evident in the Austrian case where the Ministry of Finance controls allocation of finances, despite being disconnected to the Ministries formulating policies within the realm of R&D and university reform ((European Commission, Erawatch, 2014c). This is further exacerbated by the fact that education policy is not fully integrated in knowledge triangle within Austria at present (European Commission, Erawatch, 2014i), thus creating the need for more joined up thinking. Fragmentation also exists within the Swedish case, given public and private R&D systems are separate in Sweden, with universities carrying out most public R&D (European Commission, Erawatch, 2014n: European Commission, Erawatch, 2014t). Nevertheless, governmental programmes aim to encourage public private partnerships, and greater efforts are being made in the Swedish innovation system to involve universities. However, at present, it seems too much competition exists between regions, which create an environment that restricts collaborative activities. Each country case has individual elements which are outperforming the other, yet Sweden appears to be slightly ahead of Austria, due to governments being more supportive of R&D in Sweden in comparison. Both countries are actively designing programmes and projects to stimulate collaboration; however one main lesson arising from this comparative study is the need for more funding and infrastructure for strategizing for long-term competitiveness and growth. Importantly, there is a need for more governmental support for universities and technology-transfer, and an increasing need to invest in basic research in order to maintain a successful innovation system. Therefore, increasing university autonomy, and creating opportunities for structural easing within prevailing institutional structures at system level should provide a framework upon which innovation can flourish from a practical system perspective.
Overall, comparing systems, it is clear that convergence in approaches are taking place, however it seems a leap is required in order to embrace new ideas and nodes of thinking, thus requiring further flexibility and openness within the system. Nevertheless, availability of funding is the core problem to overcome in this mission. In addition, the culture and ideology to adopt new ways of doing things is necessary. Interestingly, within the Austrian system adopting mechanisms such as tax incentives and further autonomy are elements that the Swedish system recognises it requires. Nevertheless, the structure and governance of such systems are starkly different, which may begin to shed light on why perhaps Sweden is an Innovation Leader. However, this seems strongly connected to prevailing cultures which tie closely with the institutional framework in place. Nevertheless, it is clear both systems are not without their challenges. Of most significance was the finding that structure of university systems is perhaps not as important at first glance as actual processes and cultures present. However, upon closer inspection, it seems structure has an important role to play in providing the physical infrastructure to complement an institutional framework upon which such processes can take place. Drilling down into the problem areas highlighted, it is clear that the overarching NIS and institutional framework influences how innovation will take place. In turn, this has influenced how universities respond, perhaps more reactively in the case of Austria. As such, prevailing culture has a major role to play both inside universities, and within the broader innovation system.
This study has gone some way to bring observations regarding university contribution and transformation from both sides of the innovation system, thus extending current literature by bringing the observations of various nodes together in one place. This has important implications for policy, given the findings not only highlight bottlenecks within the system, but highlight perceived issues from each actor collaborating with universities, and vice-versa. Therefore, it is anticipated that this study has pinpointed areas where future policy design can have significant impact for the growth of the innovation system, and the efficient development and contribution of universities. Therefore it is suggested that more inclusively designed studies are carried out in future to capture the collective thoughts of various actors for cross-analysis. Various issues have been raised within this study, requiring deeper analysis at individual topic level. Therefore, these two approaches towards research analysis have potential to provide practical insights for future development.
Like a rubrics cube or complex drainage system, it can be difficult to find a blockage or create conducive alignment. This study goes some way towards exploring this phenomenon, and it is clear that universities have the potential to contribute significantly to the innovation system. This study has exposed a number of barriers and enablers at the junction of collaboration. Therefore, the following conclusions and implications may be interesting for policy makers and university managers in both Austria and Sweden. Generic conclusions applicable to both country contexts will be discussed first, then unique country specific implications for Austria and Sweden will be highlighted, before drawing lessons for policy design at university and governmental level.
In both country cases, funding has been highlighted as a key bottleneck for transformation and contribution of universities to the innovation system. Availability of infrastructure is restricting the amount of collaboration that can feasibly take place, thus limiting the amount of diversified funds universities can realistically acquire. Therefore, government need to understand that targeting funding to this aim would create a positive investment for the future, enabling universities to source funds elsewhere in the system, thus potentially reducing their level of dependency on public funds. The “Valley of Death” has been pinpointed as a major inhibitor towards commercialisation of research. Therefore, targeted government funding is required to provide risk capital that is currently extremely sparse within both country cases. This should help to transform more research into products and services for the market, which is noted as lacking at present (The North Sea Region Programme Secretariat, 2013. p.5). It should also increase the returns on public investment, given too many projects have to be killed off because of lack of funding to continue their development. At present, there is also too much competition within the system, requiring strategic measures to promote collaboration. Therefore, greater alignment between regions and federal states will not only create efficiencies, but ensure knowledge transfer permeates throughout the system, thus raising innovation potential nationally, rather than within specific hotspots. In addition, the need to target more funds towards basic research was also highlighted by actors, given a lack in basic research will ultimately restrict the amount of applied research that can be carried out, thus stunting the research system. This reflects Allinson’s (University Industry Innovation Network, 2013) finding that funding mechanisms has reduced time and funds for the pursuit of new knowledge. Therefore, this appears to be a common problem beyond the case countries under analysis.
Another commonality to both country cases is that the traditional orientation and structure of universities varies greatly, which slows the process of collaboration due to bureaucracy, difficulties in identifying the right people to contact, and a lack of visibility regarding how business negotiations should take place with universities. Funding through various mechanisms has seen the implementation of TTOs which has enhanced the interface between universities and the innovation system. However, more needs to be done to enhance the business models of universities in order to further professionalise university operations, particularly with regard to management of collaborations, so that universities are able to operate more entrepreneurially, and thus enhance and extend the third mission activities in which they are involved. This includes the need for further infrastructure and human resources, which has the potential to increase commercialisation activities. Various issues were also exposed regarding the successful implementation of university transformation. Embedding entrepreneurialism within the mission and strategy of the university is imperative. In addition, strong leadership, and development of trust within the system is needed to get academics on board. Pressures to service the core missions of the university, as well as third mission activities, is facing major limitations due to available time and funding. Therefore, university managers must design solutions which are contextually sensitive to the prevailing organisational, structural and cultural environment present. The case studies analysed within this study go some way to illustrate successful methods and challenges which could be useful for benchmarking purposes.
Platforms such as the Competence Centres have been highlighted as a positive addition to both country cases’ innovation systems, given their long-term orientation and capacity to enable trust building between actors. Davey et al. (2009) also maintain that sustainable high-level commitment is required, not only with respect to funding models (found in Koryakina, Teixeira, and Sarrico’s (2012) study), but also softer aspects such as communication, motivation and time horizons of stakeholders in order to promote collaboration between actors. It is suggested that further funding is directed to support longer-term endeavours in conjunction with mechanisms designed to deliver results in the short to mid-term. Providing greater synergies and connections between policy areas could potentially enable the fruitful design of complementary mechanisms which will not only provide efficiencies, but deliver intended results. Nevertheless, knowledge transfer systems are needed within universities, and externally to communicate research endeavours with other innovation actors. Such a system could speed up the development of research by reducing duplication in the system and aligning interested industry partners with appropriate research groups for collaboration.
Significantly, two particularly unique country specific implications were also highlighted during the study. In the Austrian case it is clear that disconnection exists within knowledge triangle policies (European Commission, Erawatch, 2014i), which echoes findings by FarHorizon (2010) and the Austrian Council (2009), as even after 5 years, work still needs to be done. Therefore greater alignment in policies could potentially enhance output of the system. However, culture plays a pivotal role, and mechanisms must take account of current prevailing cultures, and strategically design systems which will promote entrepreneurial activity. In the Swedish case, further autonomy should be afforded to universities in order to overcome legal barriers pertaining to the funding of commercialisation. By providing an appropriate regulatory environment, universities will increase their performance if they are empowered to do so (Hoareau, Ritzen and Marconi, 2012).
Overall, adoption of the aforementioned suggestions should aid the design of a more flexible system incorporating synergies and mechanisms to encourage collaboration and knowledge transfer, which should ultimately lead to economic growth, and may help to overcome the European Paradox (European Commission, 2007). However, ignoring these structural issues, particularly regarding targeted funding and development of infrastructure, will ultimately stall developments within each given system. This could potentially have lasting consequences on innovation and national competitiveness as a result, if private funding does not increase to meet the shortfall (Hoareau, Ritzen and Marconi, 2012). Therefore, funding endeavours must be regarded as a long-term investment to the system, in order to reap the benefits of economic growth, and create efficiencies within the system. This study has highlighted the importance of including all actors and being sensitive to their needs, as well as having a well-functioning and stimulating enabling environment, which has been proven to be heavily influenced by the prevailing institutional framework and innovation system. Therefore, improving interactions and providing a conducive environment increases the chances of innovative activity and potential economic development, which is imperative to try to improve return on public investment. However, it is also important to balance competing objectives within the system and within universities, given the varying missions universities are expected to carry out. Therefore, this study has enabled a snapshot of how this has impacted university transformation towards becoming more entrepreneurial, and where actors collectively see bottlenecks, which, if addressed, would ultimately increase university interaction and contribution to their respective innovation systems.
These lessons can be utilised in both country contexts to redesign policies and initiatives to be conducive to universities and the wider system, in order to create greater returns, and protect and maintain the core mission of universities. Understanding the role of proximity at regional, national and international level, both geographically and culturally may be useful in order to further develop technopoles (Doloreux, 2002) such as Competence Centres, to encourage interactions and cross-pollination of knowledge between actors, and further enhance activity in both country contexts. In addition, universities can benchmark and find solutions to meet the range of demands placed upon them. Importantly, governments need to provide funding and policies that provide a supportive mechanism promoting university interaction and contribution (through technology-transfer), rather than a restraint or bolt on requirement. Taking account of the lessons learned in this study may go some way to help Austria in its endeavour to become an Innovation Leader, and help Sweden to further elevate its activity. In a globalised and competitive world, now is the time to address these challenges in order to remain competitive and ensure these innovation systems and universities continue to develop, considering university technology-transfer is underutilised in many countries within Europe (IKTIMED, 2013).
During the course of the study, several areas were identified requiring further research. It would be useful to carry out this study in more depth, including more participants, across other European countries. Considering the EU wish to solve the European Paradox, further insights at the interface between universities and other innovation actors may highlight whether similar bottlenecks exist in other country cases. This would enable better targeting of EU funds in order to service the aims and objectives of Innovation Union, in order to aid competitiveness and functionality of the system. It would also be beneficial to carry out a targeted study specifically on the bottlenecks highlighted within this study in order to look for possible solutions that could be implemented within each case country. In addition, investigating why transfer of funding between sectors is low in Sweden would be useful to determine how to improve Triple Helix interactions. The complex structure and organisation of the health system in conjunction with university hospitals requires further analysis in order to simplify the complex landscape and ease bottlenecks for innovation within the system. Also, further insights into differing governance structures are imperative to identify how influential this locus of control is. Considering Sweden places a lot of power to government agencies, and Austria has a more bureaucratic system with relatively autonomous Federal States, it would be interesting to investigate how differing institutional framework models affect output, and thus identify their adaptability and application in other systems for the benefit of innovation. This type of study would also benefit through recognition of prevailing cultures, given this has been highlighted as a key component dictating the success of mechanisms within a system, whether at micro or macro level.
I would like to thank my supervisor, Professor Karl-Heinz Leitner, for his guidance and support throughout the project. Heartfelt thanks also go to my interviewees for giving their time and expert opinions to the study. Thanks also go to everyone who provided information, suggested interviewees, supported, and guided this project. Without your help and support this project would not have been possible. Thank you!
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