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Journal of the National Research University Higher School of Economics

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ISSN 1995-459X print
E-ISSN 2312-9972 online
ISSN 2500-2597 online English

Editor-in-chief
Leonid Gokhberg

   



Foresight and STI Governance, 2016, vol. 10, no 3 is published

2016-09-23

The new issue of Foresight and STI Governance Journal (2016, vol. 10, no 3) is focused on various aspects of innovation-based development in Russian regions, results of China-2025 Foresight study, and new customer attraction strategies in the retail sector.

China is trying to become a global player in the high-tech market, and create the largest consumer market in the world. This has prompted the European Union to conduct a Foresight study to assess future prospects of China’s innovation activities. In the paper “China-2025: Research and Innovation Landscape” the authors Epaminondas Christofilopoulos and Stavros Mantzanakis present main conclusions of this project, and describe four probable scenarios of the country’s innovation development.

The increasing competition in the retail sector forces companies to look for new ways to attract and keep clients. Marisela Rodríguez, Francisco Paredes, and Gaofeng Yi in their paper “Towards Future Customer Experience: Trends and Innovation in Retail” analyse innovative approaches to increasing companies’ productivity through improved customer experience. A new model for improving customer experience is suggested, based on a synergic blend of designer vision and marketing intelligence.

In the situation of economic sanctions introduced against Russia in 2014, high-tech industries become particularly important – as major sources of import substitution on the domestic market. A key measure to support them is promoting development of specialised clusters, by encouraging networking and cooperation between all kinds of companies and R&D organisations. In the paper “Potential High-Tech Clusters in Russian Regions: From Current Policy to New Growth Areas” the authors Stepan Zemtsov, Vera Barinova, Alexey Pankratov, and Evgeny Kutsenko propose an original methodology for identifying potential clusters, and present results of its practical application in various Russian regions.

In recent years issues associated with development of “single-industry” towns became much more acute. Nadezhda Zamyatina and Alexander Pilyasov in their paper “Single-Industry Towns of Russia: Lock-In and Drivers of Innovative Search” consider this problem through analysing relevant methodologies applied in foreign countries. Their own approach is based on the “path dependence” concept, in the scope of which the authors identify factors hindering the “new industrial policy” innovative search. Potential and opportunities for stepping up innovative search in Russian single-industry towns are presented.

As complex systems, present-day cities have to smoothly adapt to the ever-changing external environment. This can only be achieved with the help of innovative management mechanisms, such as the “smart city” concept. The paper “The Smart City Approach as a Response to Emerging Challenges for Urban Development” by Marina Boikova, Irina Ilina, and Mikhail Salazkin discusses various advantages of this concept; necessary conditions for, and factors hindering its application; assesses market prospects of relevant technologies; and Russian cities’ abilities to adopt this model.

The current approach to promoting innovation-based regional development implies cooperation between government, businesses, and universities. Valery Makarov, Sergey Ayvazyan, Mikhail Afanasyev, Albert Bakhtizin, and Ashkhen Nanavyan, the authors of the paper “Modelling the Development of Regional Economy and an Innovation Space Efficiency”, introduce a new concept of “innovation space” – the totality of potential links between R&D organisations and innovative companies. Measuring such interaction is one of the more challenging aspects of innovation process analysis. According to the authors, the size (and productivity) of innovation space depend on the level of regions’ innovation activities. This is illustrated using the Republic of Bashkortostan as an example. Calculations based on the Computable General Equilibrium (CGE) model confirm this factor’s high potential importance.

 
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