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Comparing recommendations coming from the theoretical research on economic modeling of the national innovation system with suggestions based on the narrative analysis of actors from the Russian innovation system (RIS) may help design a strategy for the regulation of innovative development. The study aims to produce recommendations for the state innovation policy by examining actors’ perceptions. Narrative economics combined with elements of original institutionalism constitutes the methodological basis of the research. The paper uses qualitative methods of narrative analysis. The evidence base is narratives of the RIS actors contained in rating and specialised Russian media and Internet resources, as well as in 27 in-depth interviews, selected during the online expert sampling. According to the study’s findings, the RIS actors note a significant role of the state in the development of innovation in the narratives, but at the same time point to such problems as inconsistency of government actions, instability of innovation policy, lack of effective mechanisms for increasing financing of innovation projects. Respondents attach particular importance to business involvement in innovation, creation and promotion of entrepreneurial initiative, expansion of economic freedom. The results of the study allow identifying the most critical factors in and methods for boosting activity in the national innovation system.

The Russian innovation system is lagging behind the developed countries in terms of many parameters. In the paper, we identify the specificities and patterns of this system evolution by analysing the narratives of its actors. Methodologically, we take advantage of the synthesis of narrative economics and original institutionalism. The methods include narrative analysis, in-depth interview, and econometric analysis of how sub-indices referencing the innovation inputs and outputs influence the economic growth. The data comes in two types: qualitative ones from 27 in-depth interviews conducted from April to August 2022 and quantitative ones from the Global Innovation Index 2021. Based on a linear regression model with an innovation input and output interaction component we find that despite their proven positive impact on the economic growth, the return on innovation outputs decreases with an increase in inputs which indicates the presence of positive externalities. The research findings demonstrate that the factors “institutions”, “human capital and research”, “infrastructure”, “market and business sophistication” combined into the innovation input sub-index of the Global Innovation Index, are associated with the functioning of increasing return mechanisms in the economy. We identified the following main malfunctions of the Russian innovation system based on a qualitative analysis of in-depth interviews: lack of consistency, poor quality of institutions and legislation imperfection, science underfunding along with excessive control, selectivity of the state innovation policy. The results confirm the necessity of studying narratives for gaining a more complete understanding of how and what stable constructions are used by actors to explain the problems related to the formal and informal institutions of the Russian innovation system.

The analysis of innovation systems is a demanding task, which needs to be tackled comprehensively. Their modelling provides an indication of the formal innovative performance while the narrative analysis helps to examine relevant judgments about the rules and institutions that are key to the development of innovations. The study of the complementarity and non-complementarity of the conclusions obtained using both approaches is likely to contribute to a deeper understanding of the Russian innovation system functioning. The paper aims to analyse how the content and spread of the national innovation system narratives are interrelated with the modelling of the Russian innovation system and the most important indicators of its functioning. Methodologically, the research takes advantage of the methodological synthesis of narrative economics and original institutionalism. The research methods include narrative analysis, cointegration analysis of mutual influence between narratives and innovation indicators. The authors identify peculiar features of innovation systems’ modelling, analyse the texts, stories and other sources containing narratives about the Russian innovation system development, and based on this discover the relationship between the spread of certain narratives (the frequencies of word groups “innovative technologies”, “technology development”, “innovation activities”, “technology implementation”, “scientific schools”, “innovation policy”, “science and technology”) and innovation indicators (share of innovative goods, works, services in the total volume of goods shipped, works performed, services provided; share of expenditure on innovation activities in the total volume of goods shipped, works performed, services provided). The analysis also shows cointegration between the frequency of search queries “use of patents” and innovation indicators “number of patent application” and “number of patents issued”. The authors point to a number of limitations related to the innovation system modelling. There are some typical limitations such as availability and reliability of statistical data, methodological heterogeneity of statistics, model specification, etc., as well as some specific ones including a broad, ambiguous definition of the national innovation system, differences in the approaches to defining principal determinants, innovations immeasurability, considerations of the system connections and economies of scale, etc. Thus, the findings confirm the need for a narrative study in order to achieve an in-depth understanding of complex economic processes.