Key themes defining institutional forces for collaboration and policy mechanisms
| Key themes | Institutional forces for a collaboration | Policy mechanisms |
|---|---|---|
| Information flow between organisations |
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| Institutional cooperation |
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| Knowledge creation in HEI and RI |
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| Knowledge transfer, HPC training |
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| Ability to use HPC |
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| HPC setbacks for SMEs |
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| Transnational collaboration |
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| The competitive advantage of HPC usage |
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| National innovation policy |
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| Role of public authorities |
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| Issue of brain drain and migration |
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| Key themes | Institutional forces for a collaboration | Policy mechanisms |
|---|---|---|
| Information flow between organisations | Opportunities from academic HPC centres Promotion of HPC from academic HPC centres Low awareness of benefits from the side of the Industry | Public authorities as responsible for a systematic system for the transmission of information |
| Institutional cooperation | U-I collaboration is perceived as weak Poor knowledge transfer, low applicability to Industry Public authorities ensure free HPC training | Need to address the development and teaching of HPC competencies systematically Countries with strong industrial organisations do not require assistance from the public authorities |
| Knowledge creation in HEI and RI | Specific cases of high HPC level knowledge exist, especially among younger researchers Academic HPC centres support cross-sectoral cooperation and knowledge transfer | Support the development of new study programmes tailored more according to the HPC needs of the industrial sphere |
| Knowledge transfer, HPC training | Positive attitudes towards creativity, entrepreneurship and new technologies Industry is focussed on ICT advancements and innovation Cooperation between academic HPC centres and Industry is seen as positive | Senior researchers in some intermediary countries, particularly lagging countries, are not seen as competent to use and teach HPC. The reform of academic programmes is required |
| Ability to use HPC | The Industry obtained the ability and skill to use HPC in advanced countries Industry in advanced countries owns HPC research centres. Such ownership is an obstacle to collaboration in the academic HPC sphere Results in the exclusivity of knowledge Industry fears data disclosure and worries about data protection in the external HPC infrastructure Industry in competitively intermediate and competitively lagging countries frequently is not HPC ready – neither in awareness, type of products, nor skills | In intermediate and competitively lagging countries, the industries rely upon policy support when developing and using the HPC technology The competitively lagging countries face shadow economy and tax evasion; the level of socio-economic development is the main obstacle to HPC utilisation in Industry |
| HPC setbacks for SMEs | HPC readiness of the SMEs is low for reasons like; low awareness of the usefulness of HPC, lack of adequately trained human resources, high cost of licensed software, and rental of HPC infrastructure HPC is predominantly available through EU funding. EU-funded HPC is not open to the private sector EU projects support international networks | In competitively intermediate and lagging countries, the academic HPC centres focus on theoretical research Slow transfer of HPC knowledge to Industry EU projects demand extensive administrative work. Due to the complexity of project documentation, SMEs do not desire to consider EU project funding |
| Transnational collaboration | Industrial R&D needs in competitively intermediate, and lagging countries are addressed abroad | Weak U-I collaboration in general in competitively intermediate and lagging countries |
| The competitive advantage of HPC usage | Competitively advanced and some competitively intermediary countries demonstrate collaboration between academic HPC centres to ensure competitive advantage | The usage of HPC varies across the Danube region Presence of clustering in automotive and electronics sectors |
| National innovation policy | Existing policies support collaboration Need for working legal environment Public authorities are seen as hinderers of collaboration National innovation policy needs a vision. The lack of clear long-term goals is a weakness. The non-critical best practices imported from other cultural settings are de-motivating in competitively intermediate countries Policies supporting innovation agents who engage in clusters and networks exist in advanced countries Slow implementation of policies, too bureaucratic approach Unstable national and EU funding results in low investment/funding in science Without national support, academia in competitively lagging countries creates transnational networks due to self-initiative | In competitively intermediate and lagging countries, provision of funding for SMEs Request the training for HPC to be free and open Policy needs to ensure financial support for HPC (and related IPR) and promote innovation Too much focus on solving unemployment problems Too slow recognition of R&D profitability in competitively intermediate and lagging countries |
| Role of public authorities | Public organisations are considered an obstacle to the diffusion of technology Lack of interest in HPC in the competitively intermediate and lagging Danube region countries Solely declarative support to HPC application Lack of support for U-I collaboration Lack of support towards forming networks, especially between University and Industry, as public-private partnerships are considered fraud in some competitively intermediate countries In competitively advanced countries, the critical decision maker in national networks is in academia, while in competitively intermediate countries, the crucial actor in the networks is Industry | Policy that enables stable financing of HPC infrastructure is considered sufficient Lack of legislation, including IPR protection and enforcement (especially in lagging countries) Weak or absent Internet infrastructure in some countries Lack of long-term vision regarding innovation and short-term and long-term goals Slow and bureaucratic policy implementation Lack of recognition of HPC's effectiveness in the diffusion of technology |
| Issue of brain drain and migration | In competitively advanced countries, the talents are attracted by the high quality of life and high quality of academically exciting research groups, professors with HPC competencies, and established U-I collaboration through study programs and HPC usage during the study Competitively intermediate countries can also attract talented people but have difficulties retaining them The competitively lagging Danube region countries cannot attract or retain talented individuals from other countries, as they cannot stem their brain drain | Competitively intermediate countries are incapable of retaining talented people due to labour market issues (legislation, taxation, and incompatibility of wages with the complexity of work) Competitively lagging countries note underdeveloped Industry, inadequate political system and labour market together with underfinanced and low-quality academic sphere EU migration policy and globalisation support brain drain from competitively lagging countries |
Source(s): Own research results interpretation
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