Balance model of resource support of innovative development programs

UDC 338.3
Publication date: 30.11.2019
International Journal of Professional Science №11-2019

Balance model of resource support of innovative development programs

Балансовая модель ресурсного обеспечения программ инновационного развития

Slavianov Andrey
Cand. of Ec. Sc., Associate Professor of Department
Bauman Moscow State Technical Univercity

Славянов Андрей Станиславович
к.э.н., доцент кафедры
Московского государственного технического университета им. Н.Э.Баумана
Abstract: The imbalance in the investment sphere is an obstacle to the innovative development of the economy. Scientific organizations and industrial enterprises are not fully provided with material and financial resources. The result is an investment gap in the innovation cycle. The developed resource-saving technologies cannot be used if the enterprise does not have enough resources for their implementation. On the basis of the inter sectoral balance the model of investment balance of the innovation cycle was developed the Model allows to estimate the need for basic resources for all participants of the innovation process.
Keywords: resource support, investment, innovation cycle, balance sheet model.


Imbalance in the investment sphere is the main problem for the innovative development of the national economy. In developing economic systems, there is often an investment gap in the stages of the innovation cycle (research and development — production — consumption). The state allocates significant funds from the budget for research and development. However, enterprises, as the main consumers of scientific and technical products, cannot buy technological licenses for the release of new products, since they do not have the resources to modernize production. Disproportionately financed scientific organizations, industrial enterprises, developing new products and activities to promote it in the markets. The funds allocated for the implementation of the State program of scientific and technological development of the Russian Federation can be used irrationally and this fact makes the problem of developing and scientific justification of the system and mechanism of resource allocation within the innovation cycle urgent [1].

Problem status

Studies of domestic and foreign scientists are focused on solving the problems of resource support of only one stage of the innovation cycle.

So, Rothwell and Tovards offer to fund fundamental research and development as a priority [2]. Hodge and Grev consider it necessary to attract private capital in the development of infrastructure [3], quite a lot of work is devoted to venture financing of innovative projects [4-6].

It can be noted that the authors of the above scientific works draw their conclusions based on the fact that the innovation process proceeds under ideal conditions, which does not correspond to the realities in which the Russian economy operates at the present stage. Previously gained experience and knowledge in this area is quite problematic to use in conditions of instability in the global commodity and financial markets.

In connection with the foregoing, there is a need to develop a system of interconnected methods and tools for regulating investment activity in the high-tech sector of the economy. To create the conditions for a breakthrough scientific and technological development of Russia, it is necessary to develop a system of investment support balanced by the stages of the innovation cycle of organizations and enterprises involved in the process of creating, developing and promoting new types of services and technologies on the market.

Materials and methods

The intersectoral balance model developed by Wassily Leontief allows not only to solve production planning tasks [7], but also to distribute investments according to the stages of the innovation cycle. Consider the simplest balance model, which includes two stages of the innovation cycle — scientific research and production (table. 1).

Table 1

The balance model of the innovation process

Production Сonsumption
Domestic consumption Еnd product Gross product
Research Industry
Research х11 х12 Y1 X1
Industry х21 х22 Y2 X2
Investments IC1 IC2 IC= IC1 + IC2 IC/X
Net products V1 V2 V = V1 + V2 V/X
Gross product X1 X2 Y = Y1 + Y2 X = X1+X2

The model analyzes two aggregated sectors — industrial production and research and development. At the stage of research, many research and design organizations are engaged, the result of which is scientific and technical products (x). It should be noted that new technical solutions are often based on previously conducted research in related fields and therefore part of the scientific results is used in the development of innovative products. In the model, the domestic consumption of scientific and technical products is indicated (x11). To conduct experiments, process results, produce models, mock-ups, prototypes, equipment is required that is manufactured at industrial enterprises. The volume of equipment purchased by research organizations is indicated in the model (x21). Industrial enterprises purchase technological licenses from scientific organizations for the production of new products. The costs of acquiring technological and design documentation in the model are indicated by an index (x12). The cost of technological equipment, materials, construction and other objects is the amount indicated in the model as (x22).

Results and Discussion

To complete the innovation project, investments in research are required in the amount of

IC1  =   х11 + х21;

and in production

IC2  =   х12 + х22

Wassily Leontiev in his work “Balance of the National Economy of the USSR” [8] showed that the relations between the sectors of the economy are stable and can be predicted, on the basis of which the following conclusions can be drawn:

— the ratio of total investment in science to investment in production can be considered a constant value:

а = IC1 / IC2  — const;


— the ratio of the cost of equipment and the acquisition of scientific and technical products is also a relatively stable value:

B1 = х11 / IC1 – const;


b2 = х12 / IC2 — const;


Then, if research is financed in the amount of IC1, then investment in production (IC2) should be:

IC2 = IC1 /a.


An indicator of the quality of economic growth is the share of investment in GDP (IC / X). A decrease in the share of investments in GDP indicates the prevalence of speculative trends in financial markets.

Failure to comply with the proportions of the model can lead to the following consequences:

— investments in production are less than estimated  (IC /2 < IC1 /a), in this case part of the scientific and technical progress will remain unclaimed, technological licenses will not be realized, which will lead to a decrease in the competitiveness of the industry.

— investments in research are less than estimated (IC /1 < а·IC2 ),  in this case, part of the research and design work will be closed, investments in industry aimed at modernizing production will be focused on foreign markets, which will affect the growth of import dependence.

In addition, the structure of investment in science and production is of great importance. For research work, laboratory equipment, test benches, materials and devices are required. The lack of the necessary scientific equipment may adversely affect the timing of the entire complex of work, despite the funds allocated for these purposes.


An imbalance in investments aimed at modernizing the economy can lead to a decrease in their efficiency, loss of economic growth, and a decrease in overall competitiveness. Based on the model of Wassily Leontief, a balance model of the innovation process is proposed, which allows you to distribute investments according to the stages of the innovation cycle and organizations involved in the creation and development of new products and technologies. A balanced distribution of resources by stages of the innovation cycle significantly increases the efficiency of investments and reduces the payback period of the project.


The article was supported by The Russian Foundation for basic research, project №. 17-06-00344

Работа выполнена при поддержке Российского фонда фундаментальных исследований, проект №17-06-00344


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