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Regular version of the site

Modelling and analysis of innovation strategy patterns

Priority areas of development: economics

Research object: Regular research project continues the ongoing research activities in the field of economics of innovation. The long-term focus of the project includes the specificity of actors and actor types within innovation systems, behavioral patterns and linkages as well as factors that determine the innovation process characteristics.

Research objectives:

  • Provision of theoretical and practical concepts, methodologies, tools and data for analysing the national innovation system, and the behaviour of and interactions among its elements.
  • Study of individual actors and actor types within the innovation system, exploring and understanding the specificities of their organisation and behaviour, explaining how these features are determined and are evolving, and examining how agency is expressed in their objectives and strategies.
  • Development of policy- and strategy-relevant knowledge about innovation processes and systems, including analysis of the institutional and contextual influences upon the extent, direction, and efficiency of innovation efforts.

Specific objectives for 2017:

  • Analysis of heterogeneous reactions of firms' innovation strategies to the economic crisis
  • Analysis of innovation strategies of the research organisations;
  • Patterns of behavior of highly skilled personnel (engineers and researchers);
  • Analysis of link between the individuals' engagement into the innovation practices and the societal attitudes towards science, technology and innovation;
  • Development of complexity-based indicators of innovation performance at country level.

Empirical Base of Research:

  • Monitoring of Innovation Activities of Enterprises (HSE data collection project);
  • Monitoring of Innovation Activities of Research Performing Organisations (HSE data collection project);
  • Surveys of the activities of innovation behavior of population (HSE data collection project);
  • Surveys of competences and skills of highly skilled professionals (HSE data collection project);
  • Statistical indicators of science, technology and innovation;
  • Expert interviews.

Results of Research:

Innovation strategies and crisis:The research allowed to reveal the heterogeneity of firm reactions on exogenous shocks. Crisis impacts can differ substantially across countries, types of businesses and types of innovation. Thеre are at lеast three various scenarios on the crises and innovation. Thus, there are many empirical papers, which investigate innovative activity of different types of firms from different countries in times of crisis. However, the subject of the reaction of companies to currеnt crises in Russia has not been studiеd yet. For Russia, the this study provided empirical evidence for the link between the effects on the enterprise's innovation activity due to crisis and different enterprise's indicаtors such as numbеr of employeеs, share of innovative sales, share of the cost of innovation, markets related to development. Unlike the results availible for a number of European countries, Russian small enterprises appear to be much less innovative and more vulnerable to crisis in terms of cutting their innovation activities. Large actors (particularly state owned) are much more often to mantain the pre-crisis level of their innovation intensity.

Innovation strategies of the research organisations:In terms of theory development, a set of internationally recognized concepts in the domain of specialization of research institutions, technology transfer, particular elements of STI activity, were adapted to the Russian background and tested by means of the recent empirical base.

In terms of methodology, the study provides formal specifications of observation objects and their parameters in the context of analysis of innovation activity performed by research institutions as an outcome of systematization and refinement of respective theoretical and methodological approaches.

In terms of new empirical knowledge, the analysis was extended by empirically-reasoned conclusions on correspondence between elements of innovation behavior of research institutions and various internal and external factors of STI environment, inter alia, at the level of statistical estimations and aggregate indicators.

Behavior of highly-skilled professionals:With regard to the analysis of behavioral patterns of engineering personnel employed in organizations of the research and development sector, systematization of various organizational factors and social technologies was conducted to the behavior of engineers and researchers. Systematized theoretical concepts lay the foundation for further research in this direction. Analysis of behavioral patterns of engineering personnel employed in organizations of the research and development sector has shown that it is impossible to find an unambiguous relationship between motivation and creativity. The same can be noted for the relationship between the reward system and the results of work of scientists and engineers. Linking material incentives to performance results can lead to both positive effects and negative ones. Equally ambiguous are the relationship between material incentives and creativity, which is usually measured on the basis of the number of patents. It was also shown that the level of involvement of the top management of the organization in the implemented innovative projects is an important driving mechanism for the productivity of innovation activities of researchers and engineers. And the influence of top managers should be viewed not as individuals, but as members of a single management team. The diversity of the composition and qualities of the management team can positively influence the creativity, the reflectivity, the ability to share information, which in turn leads to higher innovation results.

Innovation behavior of population: With regard to the study of the connection between innovative practices of the population and social attitudes towards science and technology:

  • systematization of theoretical approaches to the study of innovative behavior of the population;
  • development of an operational model for analysis of social and economic determinants of the public attitudes to science, technology and innovation and their impact on the level of innovative activity of the population;
  • assessment of the level of innovative activity of the population in Russia.

Alternative metrics to innovation performance:With regard to the development of alternative approaches to the analysis of innovation activity, the possibilities of using economic complexity indexes to study the economic effects of innovations were explored. Based on the definition of economic complexity, the question of the possibility of directly taking into account the technological capabilities of the country was explored. Developing a number of works in the framework of the Triple Helix studies, original empirical data were obtained in the part of intercountry comparison for the selected set of countries.

Level of implementation, recommendations on implementation or outcomes of the implementation of Results: theresults were communicated via a number of highly praised scientific and expert platforms and international conferences, including the notable Globelics XII (Athens, Greece), XVIII HSE April Conference (Moscow), IFKAD (Saint Petersburg, Russia), and a number of research seminars. The discussion of results influenced applied projects performed by HSE in the areas of policy advice, including the projects for Ministry of Economic Development, Ministry of Science and Education, Ministry of Industry, Russian Federation.

Field of application: development of theoretical and methodological approaches for the analysis of innovation systems’ components and functions; development of empirical studies of science, technology and innovation; production of policy-relevant knowledge on the approaches for stimulating the efficiency and intensity of innovation across the economy sectors.


Scuotto V., Del G. M., Bresciani S., Meissner D. Knowledge driven preferences in informal inbound open innovation modes. An explorative view on small to medium enterprises // Journal of Knowledge Management. 2017. Vol. 21. No. 3. P. 640-655. doi
Scuotto V., Del G. M., Peruta M., Tarba S. The performance implications of leveraging internal innovation through social media networks: An empirical verification of the smart fashion industry // Technological Forecasting and Social Change. 2017. Vol. 102. P. 184-194. doi
Dyachenko E. Internal migration of scientists in Russia and the USA: the case of physicists // Scientometrics. 2017. Vol. 113. No. 1. P. 105-122. doi
Leydesdorff L., Petersen A., Ivanova I. The Self-Organization of Meaning and the Reflexive Communication of Information // Social Science Information. 2017. Vol. 56. No. 1. P. 4-27. doi
Miles I. D., Meissner D., Vonortas N., Carayannis E. Technology foresight in transition // Technological Forecasting and Social Change. 2017. Vol. 119. P. 211-218. doi
Meissner D., Günther J. Clusters as Innovative Melting Pots?—the Meaning of Cluster Management for Knowledge Diffusion in Clusters // Journal of the Knowledge Economy. 2017. Vol. 8. No. 2. P. 499-512. doi
Roud V., Thurner T. The Influence of State‐Ownership on Eco‐Innovations in Russian Manufacturing Firms // Journal of Industrial Ecology. 2018. Vol. 22. No. 5. P. 1213-1227. doi