International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 04, April 2019, pp. 382–389, Article ID: IJCIET_10_04_041
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJCIET&VType=10&IType=4
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
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CLUSTER APPROACH TO MANAGEMENT OF
COMPETITIVENESS OF THE REGIONAL
ECONOMY
G.S. Migunova, A.M. Kovaleva, O.L. Maslova
Financial University under the Government of the Russian Federation
I.S. Ampilov
Orel State University name of I.S. Turgenev
ABSTRACT
For Russia, increasing the innovative activity of industrial enterprises is one of the
most important strategic tasks, the solution of which depends on economic growth,
business development, the level of welfare of the population and the possibility of
effective integration of the country's economy into the global economic system. The
high level of competition in the world market stimulates the development of innovative
processes, imposes additional requirements on the technical and economic
characteristics of products and technologies and forces industrial enterprises to
actively apply innovations, develop new methods and approaches to the management
of innovative development.
A significant problem of regional competitiveness management is the need to
develop a methodology for such management, adequate to objective institutional goals
and objectives. Thus, the scientific problem of the research is the study of the essence,
laws, objects, factors and measures of regional competitiveness and on this basis in
the development of organizational and economic mechanism of management of
competitiveness of the regional economy.
The scientific novelty of the research is represented by the theoretical and
methodological foundations of the cluster approach to managing the development of
the regional economy, the concept of "cluster" is clarified.
The main attention is paid to the formation of regional cluster policy; the main
directions of the formation of conditions for clustering are identified; the practical
implementation of the cluster approach in the innovation sphere of the regions of
Russia is considered.
Key words: cluster, cluster policy, competitiveness, regional economy.
Cite this Article: G.S. Migunova, A.M. Kovaleva, O.L. Maslova, I.S. Ampilov,
Cluster Approach to Management of Competitiveness of the Regional Economy,
International Journal of Civil Engineering and Technology 10(4), 2019, pp. 382–389.
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Cluster Approach to Management of Competitiveness of the Regional Economy
1. INTRODUCTION
The basic competence of industrial enterprises is innovative activity and especially ways to
successfully bring innovation to practical implementation. The implementation of this
competence imposes new requirements on the content, organization, forms and methods of
management of industrial enterprises. In particular, due to the complexity and uncertainty of
innovation processes, there is a need to introduce new organizational and economic forms of
production management that expand access to innovation and require the integration of large
industrial enterprises with small and medium-sized businesses, science and education,
government agencies and public organizations. One of the main results of this process is the
formation of innovative clusters as the most effective form of organization of innovative
activity of economic entities [1].
The term "cluster" is currently one of the most popular when discussing the prospects for
the development of the Russian economy. The cluster approach is declared as one of the basic
paradigms of formation of the state and regional economic policy [2]. At the same time, it is
obvious that there is no common definition of this economic phenomenon. There is an
incorrect use of this term – in some cases, clusters are identified with industries, sometimes
industrial complexes of regions are considered as clusters [3].
The purpose of this study is to determine the economic nature of clusters, identify their
forms and types characteristic of the Russian economy, taking into account its inherent
specificity, and identify the possibility of impact on the formation of cluster formations at the
Federal and regional levels of government.
2. METHODOLOGY
It is known that the author of the methodological foundations of the cluster approach in
economic activity is the American economist Porter [4]. Under the cluster, he understands a
group of geographically adjacent interconnected companies operating in a certain area,
characterized by a common activity and complementary to each other. Reflecting the
dynamics of changes in the socio-economic system, clusters are formed, expanded, deepened,
but can also shrink over time, collapse, collapse. Such dynamism and flexibility of clusters is
one of their advantages in comparison with other forms of organization of the economic
system. At the heart of the cluster formation process is the exchange of information on needs,
techniques and technologies between sectors – buyers, suppliers and related industries [5].
The cluster in the economic literature is defined as an industrial complex formed on the
basis of the territorial concentration of networks of specialized suppliers, main producers and
consumers connected by the technological chain, and acting as an alternative to the sectoral
approach [6].
However, this is not the only approach to the interpretation of this phenomenon. A. A.
Migranyan defines the cluster as the concentration of the most effective and interrelated types
of economic activities, that is, as a set of interrelated groups of successfully competing firms
that form the "Golden section", in the Western interpretation of "diamond" – a diamond of the
entire economic system of the state and provide a competitive position in the industry,
national and world markets [7].
Although the founder of the cluster approach Porter, this approach to the study of the
processes of formation of competitiveness is used in a number of other theories [8]. In
particular, E. Leamer, J. Tolenado and D. Soulie considered the necessity of formation of the
entities of the cluster type with the purpose of realization of competitive technological, export
and other advantages of the companies included in their composition [9, 10, 11]. The
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G.S. Migunova, A.M. Kovaleva, O.L. Maslova, I.S. Ampilov
difference between their approach and the above is a narrower understanding of the essence of
the cluster.
The cluster approach is also typical for Scandinavian economists, primarily Swedish and
Finnish, due to the specific structure of the economies of these countries. The Swedish and
Finnish economies are characterized by the formation of powerful multi-sectoral cluster
formations. An example of such a meta-industrial cluster is the Finnish timber cluster, which
combines all economic activities related to forestry, logging and woodworking.
Let us turn to E. Dahmen concept of "development blocks", according to which the basis
of competitiveness is the gradual development of economic blocks, or sectors [12]. At the
same time, the actively developing sector gives impetus to the development of related
industries and sectors, ensuring overall progressive development and the formation of
competitive advantages. This approach deserves special attention in the analysis of prospects
of formation of the regional economic policy based on the cluster approach as allows to
concentrate stimulating influences on the key sectors ("blocks") of the economy possessing
potential of development and providing the coupled progress in the contacting spheres of
economy.
Also noteworthy are the theoretical developments of V. Feldman, who conducted
empirical studies of the processes of formation of cluster education in different countries and
paid considerable attention to the problems of ensuring competitiveness on the basis of the
cluster approach [13].
One of the main tasks of the modern Russian economy is the activation of innovative
processes, and in the future – the transition to innovative development. In this regard, it is
impossible to bypass the issues related to the allocation of innovative clusters as an
independent phenomenon. A.A. Migranyan gives the following definition of an innovation
cluster: "Innovation cluster, being the most effective form of achieving a high level of
competitiveness is an Association of various organizations (industrial companies, research
centres, public administration bodies, public organizations, etc.), which allows to use the
advantages of the two methods of coordination of the economic system – internal hierarchy
and the market mechanism that makes it possible to more quickly and efficiently distribute
new knowledge, scientific discoveries and inventions" [14].
On the legal website http://www.labex.ru the definition of the innovation cluster based on
the system approach to the identification of the economic essence of this phenomenon is
given [15]. Innovation cluster is considered as a complete system of new products and
technologies, interconnected and concentrated on a certain period of time and in a certain
economic space. Thus, according to this definition, an innovation cluster is a set of derivative
innovations that make it impossible to expand the economy in traditional directions.
In turn, N. P. Chetyrbok notes that innovative orientation is the main characteristic of any
cluster. In the same work the concept of innovation and industrial cluster is introduced [16].
The experience of the United States (support and promotion of the formation of
innovation clusters – the phenomenon of Silicon valley) shows that innovative (industrial)
clusters can be formed at the level of the region, where there is a high concentration of
interrelated industries.
On the basis of the considered approaches to the identification of the essence of the
cluster, its main identification features are revealed [17]:

production and technological interrelation of the companies forming a cluster;

territorial-industrial community of interrelations;
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Cluster Approach to Management of Competitiveness of the Regional Economy

availability of developed infrastructure providing transfer of knowledge and
technologies;

flexibility of composition and structure, absence of strict formal restrictions and
barriers preventing the expansion and narrowing of the cluster;
 openness of the cluster as a system.
Thus, the cluster is a system of interconnected technological and territorial community of
enterprises, organizations, infrastructure facilities, financial institutions, research,
implementation and investment firms, ensuring the optimal functioning of all structural
elements based on innovative products and technologies [18].
3. RESULTS AND DISCUSSION
The issue of determining the targets of competitiveness should be addressed in line with the
concept of sustainable development of the regional system, which involves the simultaneous
coordinated change of social and economic subsystems. In this regard, we have carried out a
multidimensional classification of the main financial, socio-economic, production and
territorial indicators of competitiveness of the regions of the Central Federal District (CFA) in
order to compare the positions of the Oryol region with other subjects of this macroregion and
substantiate the directions of increasing its competitiveness (Table 1).
Table 1 Classifier and codifier of key indicators of regional competitiveness in cluster analysis
models
Designation of
indicator variable
Indicator
1. Financial and economic indicators
Revenues of consolidated budgets of the subjects of the Russian Federation, mln. rub.
Expenses of consolidated budgets of subjects of the Russian Federation, mln. rub.
Average per capita cash income (per month), rub.
Average per capita cash expenses (per month ), rub.
Net financial result, mln. rub.
Gross regional product per capita, rub.
Consumer price index, %
2. Socio-demographic indicators
Population, thousand people
Population density, people per 1kV.km
Natural population growth rates (per 1000 population)
Number of registered unemployed (thousand people)
The share of population with monetary income below the regional subsistence level (%of the total
population of the region)
Number of higher education institutions
Number of hospital beds per 10000 population
The proportion of the urban population in the total population (%)
3. Production figures
The cost of agricultural products, million rubles.
Production of livestock and poultry for slaughter( in slaughter weight), thousand tons
Milk production, thousand tons.
The amount of work performed by the type of activity "construction", mln. rub.
Indices of industrial production (in % to 2017)
Production and distribution of electricity, gas and water, mln. rub.
The volume of shipped goods of own production, performed works and services on their own, mln. rub.
Investments in fixed capital of small enterprises (mln. rub.)
Number of small enterprises, ths.
Number of enterprises and organizations, ths.
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Х3
Х2
Х31
Х32
Х34
Х18
Х1
Х36
Х25
Х23
Х22
Х21
Х20
Х19
Х35
Х11
Х10
Х9
Х8
Х12
Х13
Х14
Х15
Х16
Х17
G.S. Migunova, A.M. Kovaleva, O.L. Maslova, I.S. Ampilov
Х5
Х4
Х7
Х6
Х4
Х24
Х26
Х27
Х28
Х29
Х30
Х33
Investments in fixed capital of large and medium-sized enterprises, mln. rub.
Indices of physical volume of investments in fixed capital (in % to 2017)
Retail trade turnover, mln. rub.
The wholesale trade turnover, mln. rub.
Indices of physical volume of investments in fixed assets in full circle (in % to 2017)
Territory, thousand km
Commissioning of the housing stock, thousand sq. m.
Number of cities
The volume of paid services to the population
Production of processing industries, mln. rub.
The population employed in the economy, thousand people.
Fixed assets at residual value, billion rubles
Calculations are made on the basis of materials of the Federal State Statistics Service of
the Russian Federation [19].
In accordance with the calculated values of six financial and economic indicators, we have
formed three clusters of regions of the Central Federal district with a clearly distinguishable
difference between the centroid values of these indicators (Table 2, 3).
Table 2 Cluster analysis of financial and economic indicators of competitiveness of the Central
Federal district
Cluster
1
2
3
Number of elements
cluster (regions)
3
4
10
Х3
25819,7
87334,5
23834,1
Centroid values of indicators (variables) in the cluster
Х2
Х31
Х32
Х18
Х1
25749,7
8324
7658,7
87708
116,1
93655
10848
9922
134681
113,2
23898,3
7882,9
7458,6
73008,6
113,4
The group of conditionally best by the calculated values of financial and economic
indicators is formed by four regions, ten regions that make the most part of the district, belong
to the group of conditionally worst, including the Oryol region and three regions, make the
group of average regions.
Table 3 distribution of regions of the Central Federal district by clusters (based on the values of
financial and economic indicators)
Region number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
The cluster number
1
2
3
3
3
3
3
3
2
2
3
1
3
3
3
1
2
Region
Kursk region
Belgorod region
Bryansk region
Vladimir region
Voronezh region
Ivanovo region
Kaluga region
Kostroma region
Lipetsk region
Moscow region
Oryol region
Ryazan region
Smolensk region
Tambov region
Tver region
Tula region
Yaroslavl region
The regions of the Central Federal district form two well-defined clusters in the space of
variables representing socio-demographic indicators of competitiveness (Table 4, 5). The first
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Cluster Approach to Management of Competitiveness of the Regional Economy
cluster includes ten conditionally best regions in these parameters, which include the Oryol
region.
Table 4 Cluster analysis of socio-demographic indicators of competitiveness of the Central Federal
district
Cluster
1
2
Number of
cluster
members
(regions)
10
7
Centroid values of indicators (variables) in the cluster
Х36
Х25
Х23
Х22
Х21
Х20
Х19
Х35
1221
2067
35
56
2,1
1,5
2,3
10,7
15,9
17,6
48,9
41,5
117,2
114,5
65,7
78,7
Table 5 Distribution of the Central Federal district regions by clusters (based on the values of sociodemographic indicators)
Region number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
The cluster number
1
1
1
2
1
2
2
1
1
2
1
1
1
1
2
2
2
Region
Kursk region
Belgorod region
Bryansk region
Vladimir region
Voronezh region
Ivanovo region
Kaluga region
Kostroma region
Lipetsk region
Moscow region
Oryol region
Ryazan region
Smolensk region
Tambov region
Tver region
Tula region
Yaroslavl region
According to the cluster analysis, the regions of the Central Federal district form three
groups with clearly distinguishable deviations of centroid values of a subset of variables
expressing production indicators (Table 6, 7).
Table 6 Cluster analysis of production indicators of the Central Federal district
Number of
Centroid values of indicators (variables) in the cluster
cluster
Cluster
members
Х11
Х28
Х5
Х8
Х12
Х13
Х14
Х15
Х16
(regions)
1
10
25819,7 25749,7 8324 7658,7 87708 116,1
25819 25749
8324
2
1
87334,5 93655
10848
9922 134681 113,2
87334 93655 10848
3
6
23834,1 23898,3 7882,9 7458,6 73008 113,4
23834 23898 7882,9
Х17
7658,7
9922
7458,6
Table 7 Distribution of regions of the Central Federal district by clusters (based on the values of
production indicators)
Region number
1
2
3
4
5
6
The cluster number
1
1
3
3
1
1
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Region
Kursk region
Belgorod region
Bryansk region
Vladimir region
Voronezh region
Ivanovo region
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G.S. Migunova, A.M. Kovaleva, O.L. Maslova, I.S. Ampilov
7
8
9
10
11
12
13
14
15
16
17
3
1
1
2
3
1
3
3
1
1
1
Kaluga region
Kostroma region
Lipetsk region
Moscow region
Oryol region
Ryazan region
Smolensk region
Tambov region
Tver region
Tula region
Yaroslavl region
According to the results of a comprehensive three-stage cluster analysis of seventeen
subjects of the Central Federal district on selected subsets of financial, economic, sociodemographic and production indicators, Oryol region belongs to the group of medium-level
competitiveness of regional regions that form the territorial and economic center of the
Russian Federation.
4. CONCLUSIONS
In this study, the role of regional authorities in the formation of conditions for reactive
clustering is justified. As the foreign experience of economic development shows, it is not
enough to recognize the fact of the formation of the cluster structuring of the economy. If the
state has the capacity to stimulate the formation of clusters with the potential for economic
development, which can act as points of growth, it is advisable to use the appropriate
economic mechanisms of public administration. Clusters objectively have all the advantages
that economic integration gives on the basis of cooperative ties.
To achieve the goals and objectives of the innovation and industrial policy of the Central
Federal district, it is necessary to form a cluster of regional type, with elements of vertical and
horizontal integration on the principles of scientific, technical, industrial and financial
cooperation [20].
The implementation of a comprehensive program of structural diversification of industry
in the regions and cities of the Central Federal district will improve the efficiency of
production and competitiveness of products through the identification and involvement in the
economic turnover of the resource and innovative potential of municipalities.
The implementation of the proposed measures will ensure the achievement of the
following important socio-economic goals:

replenish the revenues of the budgets of subjects of the Central Federal district;

to avoid mass unemployment and maintain political stability in the regions and
municipalities;

to ensure the transition to the path of intensive economic recovery;

to prevent the decline in the standard of living of a large part of the population;

to ensure the growing interest of both domestic and foreign investors in the domestic
industry;

to form optimistic expectations of a significant part of the population of the regions
and cities of the Central Federal district regarding the future of our district and Russia
as a whole.
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