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Regular version of the site

Measuring and modeling patterns of innovation activities: heterogeneity of actors

Priority areas of development: economics
2019
The project has been carried out as part of the HSE Program of Fundamental Studies.

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

  1. 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.

  2. 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.

  3. 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 2019:

In terms of analysis of strategies of participants in innovation processes:

  • research into the involvement of enterprises and scientific organizations in cooperation within the framework of the "Open Innovations" paradigm;

  • research on the scientific capital of Russian researchers and its growth drivers, including incentives and motives for career development of researchers.

In terms of developing new methods of evidence-based science, technology and innovation policy:

  • Study of the possibility and development of approaches for using market surveys to improve the efficiency of state science, technology and innovation policy;

  • Study of the specifics in the application of the concepts of economic complexity, synergy and sustainability of systems for the analysis of the effectiveness of national innovation systems.

In terms of the development of observation methodology in the field under study:

  • Study of science, technology and innovation indicators based on text-mining methods.

  • Development of approaches to measuring the involvement of the population in scientific and technological activities on the example of the Sitizen science concept.

Empirical Base of Research:

  1. Monitoring of Innovation Activities of Enterprises (HSE data collection project);

  2. Monitoring of Innovation Activities of Research Performing Organisations (HSE data collection project);

  3. Surveys of the activities of innovation behavior of population (HSE data collection project);

  4. Surveys of competences and skills of highly skilled professionals (HSE data collection project);

  5. Statistical indicators of science, technology and innovation;

  6. Expert interviews.

Results of Research

In terms of studying the features and forms of cooperation between enterprises and R&D performers within the framework of a paradigm “open innovation” the modern theoretical and empirical approaches to the analysis of open innovations (OI) have been systematized. The main directions and trends of research of the OI concept were considered. In part of the theory, there was an analysis of studies that pay attention to the interrelation of OI with the Theory of the Firm. Empirical studies were aimed at studying the relationship between in-bound and out-bound OI, dynamic theory of open innovation strategy, the role of open innovation agents in creating joint knowledge. Special attention was paid to the practice and theory of OI management at the firm level, as well as to recommendations for policies aimed at supporting and disseminating open innovation. The most popular areas of further research and limitations were noted, the overcoming of which may increase the coverage of significant topics and problems in the field of OI.

One of the objectives of the project is to systematize approaches to the analysis of scientific and technical potential of highly qualified personnel in the digital economy and the analysis of motives and incentives for the professional choice and career development in R&D (research and development). To this end, a review of the current approaches to the assessment of the scientific capital of researchers was made; the main parameters and drivers of its growth in the digital economy are identified. The concept of scientific capital is used to assess the scientific, technical and innovative potential of scientists. Technological and cognitive changes have created unprecedented conditions and requirements for research collaboration, which has become the primary tool by which scientists acquire and develop their scientific capital. The data on the main parameters of the scientific capital of researchers and on the research career development are systematized (education, skills, scientific productivity, career tracks).

In terms of studying the methodological approach to the study of the processes in the R&D sector using "business tendency surveys" a theoretical review of factors that allow measuring business climate in science and assessing S&T policies was performed. Fifty factors were identified and grouped into eight groups: human resources, facilities and equipment, information infrastructure, cooperation, finance, research outcomes, engagement with society, institutional conditions. The analysis of these factors allows giving an aggregate assessment of conditions for R&D activities (business climate in science) and diagnosing "bottlenecks" in the regulation.

In terms of developing and implementing of Economic Complexity Index we provide the Modified Economic Complexity Index (MECI) as possible refinement to two relevant complexity measures: the Economic Complexity index (ECI) and the Fitness and Complexity index (FCI), both built on the basis of bipartite country-product network data and used for the evaluation of countries’ competitive advantages and growth potentials. MECI provides an ecosystem-based design. We test the three complexity measures with respect to Balassa’s Revealed Comparative Advantage index (RCA) and the newly introduced Revealed Effectiveness Advantage index (REA) using empirical data for 41 countries. The regression analysis shows that the predictive power of the three measures with respect to GDP per capita growth improves using REA index instead of RCA. MECI demonstrates better results when compared with ECI and FCI. At the same time the results for three measures converge in the case of REA index in terms of initial diversity scores and GDP per capita correlation. MECI, however, is based on eco-systems approach and can therefore be further developed into simulations.

In termes of the search for alternative indicators for the development of science, technology and innovation, the research focused on studying of the prospects of using early warning signals as tools for assessing the sustainability and resilience of sociotechnical regimes. New theoretical and practical aspects of the application of various approaches to the search for such signals are revealed as the result of the literature review.  Some of these properties depend on the systemic characteristics of an object under observation. Based on the results, the proposed methodology of monitoring socio-technical regimes was supplemented by approaches to the identification of weak signals as an evidence of destabilisation processes in a system and a qualitative substitute for early warning signals.

With regard to the systematization of theoretical and empirical research devoted to the creation and use of new indicators of science, technology and innovation, based on new data sources, as well as new methods of analysis, current work was focused on examining and aggregating approaches regarding implementation of alternative data within the framework of the research in the field of S&T and innovation studies. From the methodological point of view, the work included the systematization of alternative data market description, relevant academic discussion, specialized case studies and current practices. The theoretical component of the research was to identify measurement prospects of the main trends of alternative data development and methods of their analysis as well as to determine the potential for application and possible challenges associated with the use of alternative data in the area of science, technology and innovation.

For development framework of measurement of public engagement with science and technology on the example of the "citizen science" conception we have analysed research literature in this field. Theoretical study of the subject was to compare different approaches to the definition of this quite contested term with multiple origins. Methodological part was arranged in order to specify indicators of public participation in citizen science and to work out the toolkit for it measurement. The new empirics provide first findings about citizen science activities of Russian population and characteristics of this social category, including the specifics of its relationship to science.

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, 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, 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.

Publications:


Del Giudice M., Garcia-Perez A., Scuotto V., Orlando B. Are social enterprises technological innovative? A quantitative analysis on social entrepreneurs in emerging countries // Technological Forecasting and Social Change. 2019. Vol. 148. No. November 2019, article 119704. P. 1-7. doi
Unger M., Marsan G. A., Meissner D., Polt W., Cervantes M. New challenges for universities in the knowledge triangle // The Journal of Technology Transfer. 2020. Vol. 45. P. 806-819. doi
Li S., Garces E., Daim T. Technology forecasting by analogy-based on social network analysis: The case of autonomous vehicles // Technological Forecasting and Social Change. 2019. Vol. 148. No. article 119731. P. 1-14. doi
Li X., Xie Q., Daim T., Huang L. Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology // Technological Forecasting and Social Change. 2019. Vol. 146. P. 432-449. doi
Ivanova I., Strand Ø., Leydesdorff L. An Eco-Systems Approach to constructing Economic Complexity Measures: Endogenization of the technological dimension using Lotka-Volterra equations // Advances in Complex Systems. 2019. Vol. 22. No. 1. P. 1850023-1-1850023-29. doi
Gonçalves Pereira C., Lavoie J. R., Garces E., Basso F., Dabić M., Silveira Porto G., Daim T. Forecasting of emerging therapeutic monoclonal antibodies patents based on a decision model // Technological Forecasting and Social Change. 2019. Vol. 139. P. 185-199. doi
Gershman M., Roud V., Thurner T. Open innovation in Russian state-owned enterprises // Industry and Innovation. 2019. Vol. 26. No. 2. P. 199-217. doi
Ivanova I., Strand Ø., Leydesdorff L. What is the effect of synergy provided by international collaborations on regional economies? // Journal of the Knowledge Economy. 2019. Vol. 10. No. 1. P. 18-34. doi
Fischer B. B., Rücker Schaeffer P., Vonortas N. Evolution of university-industry collaboration in Brazil from a technology upgrading perspective // Technological Forecasting and Social Change. 2019. Vol. 145. P. 330-340. doi
Ivanova I., Strand Ø., Leydesdorff L. The Synergy and Cycle Values in Regional Innovation Systems: The Case of Norway // Foresight and STI Governance. 2019. Vol. 13. No. 1. P. 48-61. doi
Miles I. D. Transformations of Services, in: Human-Centered Digitalization and Services. Singapore : Springer, 2019. doi Ch. 1. P. 3-15. doi
Li X., Gagliardi D., Miles I. D. Innovation in R&D service firms: evidence from the UK // Technology Analysis & Strategic Management. 2019. Vol. 31. No. 6. P. 732-748. doi