New Issue of Foresight and STI Governance: 'Smart' Strategies as a Basis for Efficient Territorial Development
The new issue of ‘Foresight and STI Governance’ (2016, vol. 10, no 3) focuses on various aspects of innovation-based development in Russian regions, the results of the China-2025 Foresight study, and new customer attraction strategies in the retail sector.
China is seeking to become a global player in the high-tech market, as well as to create the largest consumer market in the world. This has prompted the European Union to conduct a Foresight study to assess the future prospects of China’s innovation activities. In their paper ‘China-2025: Research and Innovation Landscape’, the authors Epaminondas Christofilopoulos and Stavros Mantzanakis present the main conclusions of this project, and describe four probable scenarios for the country’s innovation development.
Increasing competition in the retail sector forces companies to look for new ways to attract and keep customers. In their paper ‘Towards Future Customer Experience: Trends and Innovation in Retail’, Marisela Rodríguez, Francisco Paredes, and Gaofeng Yi analyze innovative approaches to increasing companies’ productivity through an improved customer experience. They suggest a new model for improving customer experience, which is based on a synergic blend of designer vision and marketing intelligence.
Against the backdrop 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 organizations. In their paper ‘Potential High-Tech Clusters in Russian Regions: From Current Policy to New Growth Areas’, 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 the development of ‘single-industry’ towns has become much more acute. In their paper ‘Single-Industry Towns of Russia: Lock-In and Drivers of Innovative Search’, Nadezhda Zamyatina and Alexander Pilyasov consider this problem by analysing relevant methodologies that are applied in foreign countries. Their own approach is based on the ‘path dependence’ concept, in the scope of which the authors identify factors hindering innovative search in the ‘new industrial policy’. Potential and opportunities to increase innovative search in Russian single-industry towns are presented.
As complex systems, present-day cities have to smoothly adapt to an ever-changing external environment. This can only be achieved with the help of innovative management mechanisms, such as the ‘smart city’ concept. ‘The Smart City Approach as a Response to Emerging Challenges for Urban Development’, a paper by Marina Boikova, Irina Ilina, and Mikhail Salazkin, discusses various advantages of this concept, as well as necessary conditions for and factors hindering its application. It also assesses the market prospects of relevant technologies and Russian cities’ ability 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 organizations 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. The Republic of Bashkortostan is used as an example to illustrate this. Calculations based on the Computable General Equilibrium (CGE) model confirm this factor’s high potential importance.