Intellectual Capital as a Key Factor in the Economic Development of the Region
Maria Konovalova1*, Olga Kuzmina1, Alexander Mikhailov1, Rustam Hansevyarov1 and Natalia Persteneva1,2
1Departament of Economic Theory,
Samara State University of Economics,
2Departament of Mathematical Statistics
and Econometrics, Samara State
University of Economics, Samara, Russia
- *Corresponding Author:
- Maria Konovalova
Departament of Economic Theory
Samara State University of Economics
Received date: September 06, 2016; Accepted date: September 16, 2016; Published date: September 26, 2016
Citation: Konovalova M, Kuzmina O, Mikhailov
A, et al. Intellectual Capital as a Key Factor in the
Economic Development of the Region. Global
Media Journal. 2016, 14:27.
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Modern economic development under globalization and increased competitiveness requires the availability of intellectual capital. Nowadays, intellectual capital has become one of the most demanded resources, which is explained by its ability to generate new ideas and find creative approaches to existing economic processes. Intellectual capital is developed in two ways: education – skilled personnel training, and involvement of foreign specialists. In the article that relies on existing approaches intellectual potential assessment model is formed and cÃÂ°n be applied to the regions of the country. With the help of this model the intellectual potential of the Samara region is assessed. In the article the quantity level link of gross regional product and intellectual regional potential is analyzed. Built regression model shears that intellectual capital significantly affects a regional income level. The Samara Oblast has many skilled specialists that form its intellectual capital. New educational institutions should be established and innovative projects should be funded to improve the level of the oblast's intellectual capital.
Economic development; Gross regional product; Intellectual capital
assessment methods; Intellectual potential; Investment attractiveness; Region
In a modern economy, intellectual capital is recognized as a
leading resource, availability and use of which is the basis of
individual activities, any economic entity (Organization, region)
and influence its effective functioning [1,2]. The significance of
this factor increases every day, because in the modern world, the
priority takes intellectual (creative) individual activity.
Mechanism for effective functioning of intellectual capital
is impossible without its assessment [3,4]. But at present
moment, there is no unified methodology for intellectual capital
assessment. At first it is due to the fact that there is no a unified
approach to an intellectual capital structure. Furthermore,
intellectual capital is very difficult to assess using only accounting
data, because it focuses primarily on the assessment of "past"
activity, and intellectual capital is aimed at the future.
Views on Methods for Evaluating the
Works of many scientists such as A Poltorak and P Lerner ,I
Edvinsson and M Malone , RS Kaplan and DP Norton  are
devoted to solve the problem of intellectual capital assessment.
The most comprehensive review of intellectual capital
assessment methods, in our view, is represented by КE Sveiby
[8,9]. The author allocates 25 assessment methods of intellectual
capital, grouping them into 4 categories.
Direct assessment methods of intellectual capital Direct
Intellectual Capital methods (DIC). This category includes all
methods based on identification and assessment in individual
assets or in individual components of an intellectual capital [10- 12]. After individual components or even individual assets of
intellectual capital have been assessed, an integral assessment of
intellectual capital is concluded. It's not necessary that individual
components assessment are added. More complex formulas can
Methods of market capitalization-Market Capitalization Methods
(MCM). The difference between company market capitalization
and its shareholders equity is calculated. The resulting value is treated as a cost of its intellectual capital or intangible assets
Methods of return or assets-Return on Assets (ROA) methods: Tire ratio of average company income before taxes for a certain
period to tangible assets- ROA of the company – is compared
with the same indicator as a whole. To calculate an average
additional income from intellectual capital, a received difference
is multiplied by tangible company assets. By direct capitalization
or discounting оt received cash flow we can get the cost of
company intellectual capital.
Methods of calculating score-Scorecard Methods (SC): Different
components of intangible assets or intellectual capital are
identified; indicators and indexes in a form of scores or graphs
are generated and reported. Application of SC methods is not
supposed to get monetary assessment of intellectual capital.
These methods are similar to die methods of diagnostic
Thus, all known methods of intellectual capital assessment
developed by various authors, are easily distributed into four
categories [14-16]. Relative closeness of DIC and SC methods as
well as MCM and methods of ROA should be mentioned. In the
first two cases the movement occurs from individual components
identification of intellectual capital, in the second case it happens
because of a cumulative effect.
ROA and MCM methods that offer monetary assessment, are
useful when companies are merged and in situations of purchase
and sale business. They can be used to compare companies within
the same industry. They are very good to illustrate financial value
of intangible assets. Finally, they are based on established rules
of accounting, they are easy to be communicated to professional
accountants. Their disadvantages are that they are useless for
non-profit organizations, internal departments and public sector
organizations. Tins is especially true tor MCM methods, which
can be applied only to public companies.
Advantages of diagnostic and information system and SC
methods are that they are applied at any organization level. They
work closer to the event, so the received message may be more
accurate than financial measurements. They are very useful for
nonprofit organizations, internal departments and public sector
organizations and for environmental and social objectives. Their
shortcomings are that indicators are contextual and must be
configured for each organization and for each objective, which
makes comparisons very difficult. In addition, these methods are
new and not easy to be accepted by society and managers who
are accustomed to treat everything from financial point of view.
Complex approaches generate large amounts of data, which are
difficult to analyze and relate.
Considering the concept content of an intellectual capital in a
regional context, it is reasonable to talk about the possibility of
concept application in issues of regional strategic development.
The intellectual capital can be considered as a factor of
innovation development that is proved by a direct link between
the condition of an intellectual capital and the level of regional
Calculation of the Intellectual Capital in
the Samara Region
To test methods for intellectual capital assessment we have
calculated not a monetary assessment of an intellectual capital
(capacity) of the Samara region. At present moment literature
there is no common methodology for calculating an intellectual
potential of the region, we took a standardized calculation
methodology close to the economic meaning, as well as for
calculating human development index (HDI) that was developed
in 1990 by a Pakistani economist Mahbubom ul-Hakom, under
UNESCO auspices and widely used in international comparisons.
Human development index has an ultra-integral character,
according to certain rules there are three indicators of population
life quality that are summed up in it: welfare level, that is expressed
in figures per capita income; health level that is expressed in
life expectancy rate; education level that is measured by the
literacy level and the share of young people that are getting
higher education in higher education institutions. In other words,
in a Human development index economic, environmental, and
cultural factors of people life are summarized.
Intellectual potential as well as HDI is an integral concept, but
more specialized. Methods application of human development
index calculating for assessing regional intellectual potential is
possible only it analyzed indicators are significantly corrected. In
this context human development index modification is attempted
in works of VK Levashov and MN Rutkevieh . They suggest
that two elements are fundamental in intellectual potential
assessment: science and education.
The model that was proposed by VK Levashov and MN Rutkevieh
 seems to us to be interesting, however, focusing only on the
two areas of public life may not give a complete picture about the
condition of regional intellectual potential.
The structure of intellectual capital comprises three interrelated
elements: human, structural and consumer (relationship) capital.
Analysis of education sphere condition gives an idea about the
level of human capital development, scientific -structural, but
consumer capital is not described in the model of VK Levashov
and MN Rutkevieh . Therefore, to assess intellectual potential
we offered a broad system of indicators (Table 1).
||Within the period
||The share of employed
population with higher professional education,%
||Share of costs on education
||Number of students with higher professional education per 10000 people
||Coefficient Unemployment rate,%
||The number of organizations
performing research and development
||Share of internal costs on scientific and research
development in GRP,%
||Number of PCs connected to the Internet per 100
||The specific weight of PC with Internet access,%
||Investments into fixed assets per capita, mln. rub.
||Number of used advanced
||Number of created advanced manufacturing
||Specific weight of innovative goods, works and services in the total volume
of goods, works and services,%
Remark: The table has been drawn up on the basis of the data of Federal State statistics service, available at URL: http://www.gks.ru.
Table 1: Indicators of intellectual potential of the Samara region.
Below there is an algorithm of regional intellectual potential
On the first stage of the analysis indicators were identified
that characterize basic elements of intellectual potential. A
measurement system was formed, taking into consideration that
it should not be complex; it should be easily checked and added
with sociological and statistical information.
On the second stage selected indicators were converted
into comparable kind by linear scaling method that is used
in calculating human development index. At the feedback of
an assessed indicator the calculation is made according to the
At direct connection of an assessed indicator the following
formula is used:
where: Yij − is an index of an intellectual potential indicator;
Xij − is an actual value of i-indicator;
maxXij and minXij − maximum and minimum values of an indicator
within the period among all researched regions;
i – the number of indicators.
The results are presented in the Table 1.
On the third stage five intermediate indexes were calculated with
the help of method of arithmetical average of corresponding
indicators: an index of educational potential (IEP=0,3871),
an index of social well-being (ISW=0,75), an index of
scientific potential (ISP=0,6667), an index of information and
communication component (ITС=1) and an index of relational
capital (IRC=0,7217) (Table 1).
An integral index of regional intellectual potential (IP) was
calculated by the method of weighted arithmetical average of
intermediate indexes. Coefficients weight was determined on
the base of expert assessment:
So, the integral index of an intellectual potential of the Samara
region in 2013 was equal to 0.6703.
Analysis of index dynamics of integral intellectual potential of the
Samara region is presented in Table 2. For analyzed years the index of intellectual potential of the Samara region increased more
than 2 times. The integral assessment of intellectual potential of
the Samara region 0.6703 (at maximum value of an index that
equals to 1) can be assessed higher than an average level in the
country as a whole. However, although this kind of assessment
can serve as an indicator of general state of intellectual capital,
its elements assessment are more important for the analysis of
regional intellectual capital. If we compare the elements, we can
see the imbalance of current state of the most influential element
of intellectual capital, human capital (educational potential
indicator has significant negative deviation, Table 3).
Table 2. Dynamics of the integral index of intellectual potential of the Samara region.
|Group of indicator
||Deviation from integrated assessment
|Indicators of educational potential
|Indicators of social well-being
|Indicators of scientific potential
|Indicators of information and communications component
|Indicators of relational capita!
Table 3: Elements assessment of intellectual capital, 2013, the Samara Region.
The value of regional intellectual potential, the degree of balance
between its structural elements are very important indicators
that have a significant impact on the amount of gross regional
In the article on the basis of an econometric model the link of
GRP level is analyzed, general indicator of regional economic
activity, and regional intellectual potential are also analyzed.
As an effective sign Y is examined as a volume of gross regional
product (mln. rub.).
14 factor signs, indicators, are allocated, that reflect individual
aspects of regional intellectual potential of the Russian Federation
The population size is 72 units (Russian Federation subjects).
They included mainly regions and republics. National territorial
subdivisions were not included as separate units because there
was no official statistical information.
5 factors groups were formed including specific criteria, indicators
of this or that phenomenon.
Factors of an educational level of the population:
X1- The share of employed population with higher education,%;
X2- The share of expenses on education in the GRP,%;
X3 -Number of students with higher professional education per
In this group the volume of GRP is closely correlated with die
share of employed population with higher education (ryX1=0.586).
In general, each factor in this group has a direct relation with
a productive criterion that confirms the thesis about the rote
of education in economic development (high level of higher
education causes higher labor productivity and, as a consequence,
a higher salary that is taken into account when GRP is calculated).
X4 -Gini Coefficient;
X5 -Unemployment rate,%.
The Gini coefficient is a deviation indicator of actual incomes
from absolute equality in incomes distribution. The higher its
value, the higher its inequality degree, Tins indicator actually
reflects disproportions in benefits volume. It is very closely
correlated with the volume of GRP (ryX4=0.772). The relation with
an unemployment level has a reverse character because a high
percentage of the unemployed in the region worsens business
activity and reduces the rates of economic development.
Factors of scientific activities:
X6- Number of organizations implementing scientific research
X7- Share of internal costs on Scientific and Research Development
X8 -Internal costs on Scientific and Research Development in GRP,
Each of these factors has a direct relation with the criterion Y. The
closest connection was marked with the factors X6 (ryX6=0,010)
and X8 (ryX8=0,900). It proves the role of research capacity in the
region to raise the level of economic development.
Factors of info urination and communication technologies
X9 - Number of PCs per 100 employees;
Xl0 -Specific weight of PCs with Internet access,%;
X11- Number of PCs per 100 employees with Internet access,
The transition of Russian economy into information development
way is urgent, because with the help of information and
communication technologies (ICTs) the possibility of free
information exchange, business correspondence is created,
borders of marketing information communication are widened;
payments and sale of goods (services) are implemented.
Information and communication technologies are impossible
without appropriate equipment, personal computers (PCs). Each
factor in this group has a positive pair correlation coefficient with
the volume of GRP. The closest relation is marked with a factor
Innovation and investment factors:
X12-Investments in fixed assets per capita million rubles;
X13-Тhе number of advanced manufacturing technologies;
X14-Specific weight of innovative goods5 works and services in
These indicators in a pure form characterize quantity results of
regional innovation development, and each of them is directly
related to the volume of GRP. The highest value of a pair
correlation coefficient is observed by the factor X13 (ryX13=0,704).
The value of actually used innovative technologies gives rise to a
high level of regional product.
Selected factors-arguments must be relatively independent on
each other. There should not be a significant correlation relation
between them, i.e. there shouldn't be multicollinearity. The
notice of multicollinearity is provided by building and analyzing
the matrix of pair correlation coefficients (Table 4). In order to
eliminate multicollinearity build a matrix of pairwise correlations
and eliminate if necessary overlapping factors based on the
performance of the following system conditions:
Table 4: Matrix of pair correlation coefficients.
where: r – correlation coefficient;
xi, xj – factors;
y – the resulting figure.
Multicollinear factors are in bold in the table.
For the analysis only statistically significant factors must be taken
that are related with a modeled indicator.
The multifactor regression model that describes GRP dependence
on regional innovative development factors has the following
Y=-454688 + 14097,6.X6 + 6,l.X12, (4)
where: X6-The number of organizations that conduct research
and development, units;
X12-Investments in fixed assets per capita, million rubles.
Multiple correlation coefficient in a model is 0,949. In the regions
variation of GRP is stipulated by a variation of factors that are
included in the model (90,0%), and by a variation of other factors
that are not included in tins model by (10,0%).
The increase of scientific organizations in the region by 1 unit
leads to GRP increase by 14097,6 million rubles in average. Rising
levels of investment by 1 million rubles per person leads to GRP
increase in average by 6,1 million rubles.
A similar study of GRP dependence on innovation development
factors was conducted in the Samara region. As the object of
the study was narrowed down to one Federation subject, we
supposed that it is necessary to build й temporal data model.
Originally to build a model the same 14 factors were used,
which had been presented earlier. To get correlation coefficients
characterizing cause and effect link between studied series we
should get rid of false correlations that is caused by trends in
each row. There are several ways to get rid of it; we will use
the method of inclusion a time factor into a regression model
(t). The advantage of this method is that it takes into account all
the information that source data contains (without losing part
of observations and without substituting variables by consistent
differences), and also it allows you to assess parameters by Least
As a result of a selection procedure, two factors remained
significant the same that were included in the model (4).
However, taking into account multicollinearity between them,
two separate models were built (5) and (6).
Model of GRP of the Samara region dependence on the
number of organizations that implement scientific research and
Y=-276800,6 + 7608,7.X6 + 663l5,7.t. (5)
When the number of scientific organizations in the region
increase by 1 unit, GRP grows by 760S.7 million rubles. Factors
that are included in the model explain 97,3% of annual variation
Model dependence of GRP of the Samara region on investment
volume per capita (Xl2):
Y=104243,6 + 6,6.X12 + 35218,2.t. (6)
With an increase of investment levels by 1 million rubles per
person there is a GRP increase in average by 6.6 million rubles.
Determination model coefficient is 99,4%.
Representation of the Impact of
Intellectual Capital in the Samara
Based on obtained data we can conclude close quantity relation
of scientific potential indicators of the region and its level of
GRP. Tins fact is confirmed not only by built models, but also
by international research in this area, So, in a survey of 192
countries the World Bank concluded that only 16% of economic
growth is stipulated by physical capital (equipment, buildings,
and industrial infrastructure), 20% is stipulated by natural capital,
the remaining 64% is linked to human and social capital. Most
developed countries get up to 40% of gross national product due
to effective education system development.
In terms of investment attractiveness and willingness to build
their own intellectual potential of the Samara region holds a high
position among Russian regions.
The Samara region is included among the strongest industrial
regions of countries with diversified economy. The core of the
economy is the high-tech manufacturing with high added value;
car-manufacturing, aviation and space complex, industries
with high processing in raw-material industries, chemistry
and metallurgy. Introduction of innovation technologies is an
essential condition for their development, modernization that
is based on technical upgrading, and innovative management
Today the Samara region refers to the regions of Russia where
the complex of necessary conditions is formed tor successful
modernization and tor a new innovation economy construction.
Leading positions of the region in this area are confirmed by high
ratings of independent experts:
3-rd place among die regions of the Volga Federal District
and 11th place among the subjects of the Russian Federation
according to the level of innovative capacity and to a complex
assessment of rating agency "Expert RA" in 2013;
8-th place in the ranking of innovative Russian regions for
the purposes of monitoring and managing the Association of
Innovative Regions of Russia.
In 2013 in the Samara region there were innovative products
that cost 239,0 billion rubles. The share of innovative products is
22,9% and has exceeded an average Russian level by 3-4 times.
The expenses on research and development in 2013 made 23.6
billion rubles. This is by 26,9% more than in 2011 (18,6 billion
dollars). The share of domestic costs on research and GRP
development in the Samara region is about 2% (for comparison,
the share of domestic costs on GDP research and development in
Russia more than 1%).
According to the results of 2013 the Samara region is the leader
among Russian regions of the Volga Federal Distinct and in number
of key indicators of scientific and innovative development:
4th place in Russia and 2nd place in Volga Federal District by
share of costs on technological innovation in the total volume
of shipped goods, performed works and services (6,3%), as well
as the share of innovative goods, works and services in the total
volume of shipped goods, performed works and services (22,9%);
5th place in Russia and 1st place in Volga Federal District by share
of organization costs on technological innovation (65,8 billion
1st place in Russia and 2nd place in Volga Federal District by
the volume of shipped innovative goods, works, services (239,0
6th place in Russia and 2nd place in Volga Federal District by
domestic costs on research and development (18,9 billion
dollars), as well as by a number of new used technologies (7,3
7th place in Russia and 2nd place in Volga Federal District
by a number of personnel that is engaged in research and
development (16.7 thousand people).
Intellectual property is created, rights on it are consolidated:
among the regions of RF the Samara region was in the following
places of applications in 2013:
In utility models- on the 5th place (Volga Federal District-2nd
In inventions- on 10th place (Volga Federal District-3nd place);
In trademarks and service marks- 10th place (Volga Federal
In the region there are a number of organizations specializing in
the field of legal protection and use of intellectual property, 26
patent attorneys work more than in any other region of Russia,
with the exception of central legions of Moscow, St. Petersburg
and the Moscow region.
Share of innovation companies amounted to 5,4% in 2013.
The cost of technological innovation made 65, 8 billion rubles in
2013, which is almost 4 times higher than the volume in 2011.
The main funding source on technological innovation are own
organizations funds (47, 5%).
In 2013 in the Samara region 11 organizations were engaged to
create advanced manufacturing technologies, they created 21
In 2013 organizations used approximately 7,3 thousand advanced
manufacturing technologies, of which:
33,7% in the field of manufacturing, processing and assembling;
44,5% in the field of communication and management;
14,9% in the field of design and engineering.
In the Samara region legal, regulatory and institutional base
was formed that covers the use of all forms of state support
for innovation activities that are stipulated by the legislation.
The diversity of support forms of innovative projects and
developments in the Samara region includes giants, subsidies,
loans, share capital, со-financing projects with federal institutions,
consulting and organizational support.
In the region systematic actions were implemented to form
an effective innovation infrastructure, creating a platform for
completed innovative cycle.
By the initiative of Samara region Government infrastructure
organizations system was created by regional budget means,
with the assistance of federal funding to support and promote
innovation developments – Innovation Fund of the Samara
region, a Regional innovation center, Regional Venture Fund,
Technopark, business incubators, innovation development
center and cluster initiatives, Guarantee fund, Information and
consulting agency, microfinance and other organizations.
From 2012 year the Samara region is a member of the Association
of Russian innovative regions. This opens up additional
opportunities for the region of interregional cooperation in terms
of innovation development, especially experiences exchange in
the field of favorable legal, economic and social environment
creation to develop innovations on the territories of Russian
Federation subjects, to develop and promote joint projects of the
Association members and other opportunities within common
The main objectives of Samara region Government are searching
for new formats and capabilities to support latest developments
introduction into manufacturing, to build communications between the parties of innovative activity, to increase transfer of
scientific and technical developments into a real economy sector,
to prepare innovative companies of the Samara region for the
entry of private capital and commodity markets.
To enhance innovation activity and emergence of new and
innovative businesses the Samara region works in the field of
major infrastructure projects implementation; Technopark is
being created in the sphere of high technologies "Zlugulevskaya
Valley", a special economic zone of an industrial type.
The basis of scientific potential of the Samara region is higher
education, academic science and scientific units of industrial
enterprises. In the field of research and development there are 61
scientific research organizations in different areas in the region.
Research in the field of fundamental sciences is coordinated
by Samara scientific centre of the Russian Academy of Sciences
(SamSC), which unites 8 and 3 research institutions of the Russian
Academy of Sciences.
In the Samara region 28 education institutions of higher
professional education prepare specialists, 17 institutions are
state. The number of students in the universities in 2012/2013
was 141.7 thousand people .
A special role in the process of modernization and economy
technological re-equipment of the Samara region are created
by small innovative enterprises in the universities, which are a
kind of bridge between theoretical science and industry. Thanks
to initiating activities of innovative infrastructure organizations
the Samara region took a leading position in Russia according to
the number of functioning small innovative enterprises in the
universities (in terms of realization of Federal Law 217), there
are 62 economic companies with the participation of 6 higher
education institutions of the region.
In 2013, a huge project was initiated on innovation infrastructure
development -project of Technopolis "Gagarin Center"
establishment in Samara as a university research-and-production
campus with a unified world-class scientific and industrial,
educational, residential, cultural and consumer area.
Tills project will develop as a legacy of FIFA World Cup 2018 after
that the ground that is joined to the complex will be a part of the
Technopolis including a stadium and infrastructure. On a unified
ground there will be a university campus, residential buildings
and dormitories tor students, graduate students, teachers and
researchers, business incubators, technoparks, engineering
companies, innovation support organizations, scientific and
technical centers of large global companies, innovation and
R&D centers, facilities for pre-college education and pre-school
preparation, Congress Exhibition complex, as well as objects that
provide a unified socio-cultural space and sports space.
Innovation activity will be based on the integration of
accumulated development and competency of leading scientific
schools and territorial clusters of the Samara region in the fields
of mechanical engineering and machine-tool construction, space
missile and aerospace, automotive, chemical and petrochemical
industry, power and energy, nanotechnologies, biotechnologies
and medicine, IT-technology, transport systems and logistics.
It is supposed that developed mechanism of innovation activity
support in the Samara region will soon allow to see the results
of your work as coordinated work of established institutions
of innovation development, large innovation projects with
tangible results, new competitive businesses based on scientific
and technological development, effective "corridor": demandsuggestion,
changes in the economy structure in favour of
innovative industries, attract federal funding for innovative
Titus, we can conclude that the most important condition tor
socio-economic development of the region is intellectual capital
To realize this condition not only a comprehensive regional
programme is required, that takes into account multifaceted
nature of this phenomenon, but also a high level of financial
investment in its major areas, as well as effective mechanisms
tor tins programme implementation. One of these mechanisms
is to conduct regular monitoring of regional development level of
intellectual capacity, that allows on the example of the Samara
region to determine not only achievements but also unresolved
problems and unused reserves.
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