ISSN 1995-459X print E-ISSN 2312-9972 online ISSN 2500-2597 online English
Editor-in-chief Leonid Gokhberg
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2014. vol. 8. No. 1
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Innovation and Economy
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6–23
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Co-operation, knowledge co-creation and exchange are core components of modern economic models of innovation development. Intensity and efficiency of linkages is widely considered as one of the major determinants of innovation system performance. This paper presents empirical estimates of the scale and character of interactions between companies and research organisations in the Russian economy. The data are derived from the surveys of 1000 enterprises (2011) and 1000 research organisations (2012). The questionnaire is designed to allow characterization of cooperative practices and knowledge demand and supply. One of the key findings on the demand side is significant heterogeneity of involvement by sectors in the knowledge transfer process. Specific sectors (e.g. petrochemistry, equipment manufacturing) are tightly integrated with R&D institutions, while others (e.g. consumer goods, wood processing industries) are not linked to the Russian S&T development complex. This diversity of practices is partly determined by the overall allocation of resources within the economy as well as specific competition regimes that limit short- and medium-term benefits from R&D. Similarly, on the knowledge supply side, R&D organisations do not treat technology transfer as a priority strategy for sustainable development. Indeed, they focus on intellectual services instead of R&D, that is, on consulting andmodification of existing technologies. Among innovation-active companies, only 14% rely on the R&D results of Russian research centers. Of those actually engaged in co-operation, 12% of companies indicate implementation of new-to-the-world products or production processes and 29% new-to-the-country innovations. Generally, low demand for R&D meets limited novelty of research results produced by the research organisations (compared to the technologies available on the global markets). Thus there are limited enclaves of efficient co-operation. These are mainly grouped around traditionally arranged institutional linkages as well as existing allocations of financial resources across the economic sectors. |
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24–32
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User innovation is the result of information asymmetry. Manufacturers are not completely aware of consumer needs; as a result, skilled users can improve products and suit them to their needs. Users best judge what will lead to commercial success, and they have long been recognized as a valuable source of knowledge to harvest for future innovation. Therefore, firms now involve customers in developing product ideas that are usable and valuable. The challenge is that valuable consumer-related knowledge is widely dispersed, and aggregating it is a complex and expensive task. However, the development of ICT opens up new possibilities, in particular, for innovation communities linking users with different needs and experiences. Interaction with users allows companies to integrate distributed knowledge, which gives the opportunity to improve the functionality and quality of the developed products. This paper analyses trends of user innovation development, their motivations to participate in innovation communities, the benefits that the company can gain from interaction with these communities, and the risks associated with a particular focus on the needs of a limited or overly wide range of consumers. It provides cases of user innovation in a number of sectors: software, hardware, construction, sports, medicine, fashion and design. The authors conclude that innovation communities are a powerful tool allowing integration of the dispersed knowledge of users into strategic decision making. The knowledge generation of inputs from innovation communities is facilitated by new analysis and data mining tools that make it easy to visualize and detect structures in virtual communication. The use of such instruments has large innovation potential if companies succeed in integrating real life conditions into technical innovations. |
Science
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34–51
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Most research on R&D internationalisation focuses on comparative analysis of location factors at the national level of analysis. Very little work, however, has taken place in this field for the sub-national regional location behavior of multi-national enterprises (MNE). The paper contributes to the existing research by providing evidence on the determinants of foreign technological activities at the sub-national level for Germany, which hosts the largest share of foreign R&D within the EU27 and features the highest cross-regional dispersion of patented research. Using a pooled count data model, we estimate the effect of various sources for externalities on the extent of foreign technological activity across regions. Particular attention is paid to the role of local knowledge spillovers, technological specialization and diversification. We differentiate foreign and domestic sources of specialisation and account for region and sector-specific influences. This is the first time that the ‘cross-border-ownership’ principle to measure R&D internationalisation is combined with regionalised patent information. To verify our findings we develop hypotheses. In particular, we expect and find that foreign technological activity is attracted by technologically specialised sectors of regions. In contrast to current empirical work, this effect applies both to foreign as well as domestic sources of specialization, although effects on foreign specialization seem more significant. We expect and find the same for science-industry spillovers. We postulate a negative impact of domestic specialization on foreign technological activities and a strong positive effect from diversificationspillovers, by comparison with specialisation spillovers, but these hypotheses are rejected. We find that the direction of the specialisation effect depends on dominance in the position of domestic firms as well as on the balance of knowledge flows between them and foreign actors. |
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52–65
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Biotechnologies are a priority area of development due to the scope of global challenges and social problems they help to resolve. There is demand for updated information about the the current state of research and challenges faced. This paper discusses the potential of patent analysis and surveys the Russian biotechnological market with both quantitative and qualitative methods. It reviews key statistical and analytical findings of empirical research. The main finding is that the Russian biotechnological market has a relatively high level of dependence on foreign technologies: among biotechnological patents published in Russia in 2012, a third was granted to non-residents. In Russia, foreigners are active in patenting universal methods and techniques useful for biotechnological advancement. This may constrain future Russian organizations’ access to results and methods and therefore block some directions of biotechnological research within the country. Among other challenges, are the following: a low involvement of the Russian commercial sector in developing biotechnologies, a lack of cooperation between the segments of the market, and a disadvantaged position of some subfields, such as eco- and aqua biotechnologies and bioenergy. By using patent data, we identify active actors contributing most significantly to progress of biotechnologies in Russia, and we focus on dynamically developing subfields, such as biomedicine and pharmaceuticals. |
Master Class
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66–75
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Causal layered analysis (CLA) is a key tool for Deep Futures approach, which is seen by numerous experts as a prospective trend in evolution of Foresight studies. It reveals hidden basic prerequisites for actual incidents thus providing an information basis for the making efficient decisions. The paper considers the nature, features and possibilities of CLA drawing on the works of French philosophers Gilles Deleuze and Felix Guattari who offer the organic metaphor of the rhizome as a way to understand the hybrid and multiple nature of reality. In this relation it argues that CLA is a method of the multiple that offers a process–theory of knowledge that facilitates new becomings and alternative futures. It makes the case that agency and social learning are enhanced through understanding human contexts as layered and dynamic. CLA is an ideal vehicle for articulating this insight and enabling futures practitioners in their work to empower stakeholders to realise their preferred futures. Concepts have effects and therefore can be understood best through application and reflection. CLA’s uses can be in the academic sphere as taxonomy or in the applied sphere of process method in which it functions pedagogically as a critical facilitator of libratory consciousness and the social learning. Thus it treats any singular projection of reality with suspicion, instead embracing the plural as the creative inversion of given context. In this way structure becomes flexible and open to transformation whilst agency finds itself located in structure so as to critique and influence it in ways that make it more reflective of optimal current and future possibilities. |
Events
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76–81
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The international research workshop, hosted by the (HSE) Institute for Statistical Studies and Economics of Knowledge in November 2013 at the Higher School of Economics addressed the growing need to integrate quantitative methods in Foresight projects. The main topic was the creation of a sustainable and reliable information and analytical database for use by stakeholders.In Russia, database development has been encouraged by the establishment of a national system of technological forecasting, which emerges from the increased demand for quality in forecasting research. Presentations were made by world renowned experts — representatives of the EU Joint Research Centre — Institute for Prospective Technological Studies (JRC-IPTS); Delft University of Technology, the Netherlands; Finland Futures Research Center (FFRC), the University of Turku, Finland; HSE and other organizations. They presented findings about best practices in quantitive research and the newest ICT-based tools in Foresight studies worldwide. These will be used in preparing a scientific and methodological base for the next round of Russia’s Long-Term S&T Foresight. Workshop participants discussed the prospects and challenges of integrating qualitative and quantitative methods in Foresight analysis. International experts described the potential for applying modeling techniques and data visualization for promising technologies and products, presented state-of-the-art simulation tools for developing quantitative scenarios for S&T, and shared experiences in the use of online games in future studies. The development of these and similar techniques, in the view of the participants, provides a greater space forimproving the Foresight methodology and the cooperation of specialists in qualitative and quantitative methods. It isassumed that in the medium term, these tools will be a partof the “gold standard” for any definitive Foresight study. Most experts agreed that the integration of qualitative and quantitative methods enriches the Foresightmethodology and increases synergies from mutual learningof specialists in collaborative projects. |
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