ARTÍCULOS ORIGINALES
ISSN 2389-8186
E-ISSN 2389-8194
Vol. 9, No. 1
enero-junio de 2022
doi: https://doi.org/10.16967/23898186.766
pp. 23-34
rpe.ceipa.edu.co
*PhD in Economics. Ulyanovsk State University, Ulyanovsk, Russia. E-mail: pinkovetskaia@gmail.com. ORCID: 0000-0002-8224-9031.
Google Scholar: https://scholar.google.com/citations?view_op=list_works&hl=ru&user=-ktJB3oAAAAJ. Scopus Author ID: https://www.
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Growing and declining enterprises:
Russian regional information
IULIIA PINKOVETSKAIA*
ISSN 2389-8186
E-ISSN 2389-8194
Vol. 9, No. 1
enero-junio de 2022
doi: https://doi.org/10.16967/23898186.766
COMO CITAR ESTE ARTÍCULO
How to cite this article:
Pinkovetskaia, I. (2022). Growing
and declining enterprises:
Russian regional information.
Revista Perspectiva Empresarial,
9(1), 23-31.
Recibido: 21 de diciembre de 2021
Aceptado: 28 de marzo de 2022
ABSTRACT Objective. To evaluate the values of indicators describing the specic weights
of growing and declining enterprises in the total number of active enterprises in Russia in
2020, as well as the number of growing enterprises and declining enterprises per thousand
people living in each of the Russian regions. Methodology. The methodology is based on the
models, which are density functions of normal distribution. Results. The research proved
that growing and fading enterprises are relatively rare among commercial organizations,
and there was a signicant dierentiation through the regions of the discussed indicators.
The regions with the maximum and minimum values of indicators are given. Conclusions.
The paper adds new knowledge about growing and declining enterprises in Russia. The work
results can be applied by governments and public organizations when justifying measures
to support enterprises characterized by an increase in the number of employees.
KEY WORDS Growing enterprises, declining enterprises, business demography, number
of employees.
Empresas en crecimiento y en declive: información regional rusa
RESUMEN Objetivo. Evaluar los valores de los indicadores que describen los pesos
especícos de las empresas en crecimiento y en declive en el número total de empresas
activas en Rusia en 2020, así como el número de empresas en crecimiento y en declive por cada
mil personas que viven en cada una de las regiones de Rusia. Metodología. La metodología
se basa en los modelos, los cuales son funciones de densidad de distribución normal.
Resultados. La investigación demostró que las empresas en crecimiento y en declive son
relativamente escasas entre las organizaciones comerciales, por lo que hay una diferenciación
signicativa a través de las regiones de los indicadores en discusión. Se presentan las
regiones con los valores máximos y mínimos de los indicadores. Conclusiones. El trabajo
aporta nuevos conocimientos sobre las empresas en crecimiento y en declive en Rusia.
Los resultados del trabajo pueden ser aplicados por los gobiernos y las organizaciones
públicas a la hora de justicar las medidas de apoyo a las empresas que se caracterizan
por un aumento del número de empleados.
PALABRAS CLAVE empresas en crecimiento, empresas en declive, demografía empresarial,
número de empleados.
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ISSN 2389-8186, E-ISSN 2389-8194
Empresas em crescimento e declínio: informações regionais russas
RESUMO Objetivo. Avalie os valores dos indicadores que descrevem os pesos
especícos das empresas em crescimento e em declínio no número total de empresas
ativas na Rússia em 2020, bem como o número de empresas em crescimento e em
declínio por mil pessoas que vivem em cada uma das regiões da Rússia. Metodologia.
A metodologia é baseada em modelos, que são funções densidade de distribuição
normal. Resultados. A pesquisa mostrou que negócios em crescimento e declínio são
relativamente raros entre as organizações empresariais, portanto, há uma diferenciação
signicativa entre as regiões dos indicadores em discussão. São apresentadas as
regiões com os valores máximos e mínimos dos indicadores. Conclusões. O trabalho
traz novos insights sobre empresas em crescimento e declínio na Rússia. Os resultados
do trabalho podem ser aplicados por governos e órgãos públicos ao justicar medidas
de apoio às empresas que se caracterizam pelo aumento do número de funcionários.
PALAVRAS CHAVE empresas em crescimento, empresas em declínio, demograa
empresarial, número de funcionários.
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Revista Perspectiva Empresarial, Vol. 9, No. 1, enero-junio de 2022, 23-31
ISSN 2389-8186, E-ISSN 2389-8194
Introduction
Commercial organizations (enterprises) can be
divided into three groups in the Russian economy
in recent years, depending on the change in the
number of their employees. First group includes
enterprises in which the number of employees has
increase in the number of employees. Accordingly,
third group includes enterprises with decreasing
number of employees. Further development of the
Russian economy is associated with increasing
volume of goods and services production, which
requires rational distribution of labor resources
between enterprises. Given this, suggest to discuss
such relevant problem as estimating the number
of enterprises belonging to each of these groups.
economies, because they have a disproportionate
ability to generate additional production and
small proportion in the total number of enterprises
through high-income countries, they account more
than half of the increase in output and employment
in these countries (Grover, Medvedev and Olafsen,
2019). Authors assumed that in developing
countries, enterprises with high growth rates could
become an important link for the implementation
of economies (Amorós, Fernández and Tapia, 2012;
Aggarwal and Sato, 2015).
Several studies show that the share of
enterprises with high rates of growth in the
economically developed countries. So in the paper
Bravo-Biosca, Criscuolo and Menon (2016) shown
that the share of these enterprises is 3 % in Austria
and Norway and about 6 % in Spain and the United
Kingdom. In Germany, Italy, the Netherlands and
Poland, share of large and medium enterprises
with high rates of development did not exceed 2 %
higher (about 10 %) was the share of such
1Data about 2021 year are not gathered by statistics service in Russia because these data are included one time in two years.
enterprises in the Republic of Korea (Choi et al.,
2017), and the United States of America (Decker et
enterprises seek to achieve production growth by
launching new products, attracting customers or
have the combination of these factors. Cusolito
and Maloney (2018) argue that production growth
by demand shocks, uncompetitive markets and
political conditions. The predominance among
fast-growing organizations of large enterprises
that are not specialized in certain types of activities
(2019).
In modern studies, along with growing
enterprises, there are also those in which there is
Such enterprises are called fading businesses. The
most interesting are works of Ascigil et al. (2008),
Park et al. (2019), and Reynaud (2010).
Main attention in domestic studies of
enterprises that provide a high rate of increase in
the number of employees and production volumes
was paid to the so-called “gazelles.” These include
large and medium enterprises that have been
that such enterprises are not shown widely in our
contribution to the economy of their regions, as
well as to the active introduction of innovations
(Bozhko, 2020; Yudanov, 2010). Kuzyk, Simachev
and Fedyunina (2020) shows participation of
fast-growing enterprises in various countries
economic activity. Attention is drawn to their large
export activity and orientation to the markets of
Asian countries. It should be noted that Russian
publications do not pay enough attention to the
declining enterprises. Analysis of peculiarities
development of growing enterprises in the regions
was not considered.
Purpose of this paper is to evaluate the values
and declining enterprises in the total number of
active enterprises in Russia in 20201, as well as
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ISSN 2389-8186, E-ISSN 2389-8194
the number of growing enterprises and declining
enterprises per thousand people living in each
by region seems more logical than absolute ones,
differences in population, namely, people are the
main consumers of goods and services generated
by enterprises.
Methodology
When determining the number of enterprises
belonging to the growing and declining ones, it is
proposed to use threshold values. The structure
of growing enterprises includes three types of
them, which are characterized by an increase
in the number of their employees: (i) with high
growth potential — had increase in the number
of employees of at least 10 % on average over the
past 3 years; (ii) fast-growing — had over the past
3 years an increase in the number of employees
more than 20 % on average per year; gazelles —
enterprises aged 4 and 5 years with high annual
increase in the number of employees of more than
20 % over a three-year period.
Enterprises that have been operating for at
least three years and have experienced an average
reduction in the number of employees by more
than 15 % annually for two consecutive years are
considered to be declining. The research process
data describing number of active, growing and
declining enterprises, as well as the population
in each of Russian regions. At the second stage,
enterprises in the total number of active enterprises
in Russia were. At the third stage, determined
indicators that characterize the number of growing
and declining enterprises per thousand people
living in each of Russian regions. At the fourth
stage, evaluated distributions of these indicators
of these indicators for the regions and located
ranges in which the values of these indicators are
for most of them. At the sixth stage, carried out
comparative analysis, during which the regions with
minimum and maximum values of the indicators
were established.
82 regions of Russia as the initial information.
Also evaluated following four indicators that
characterize relative number of enterprises in
in the number of employees in enterprises by
enterprises in the total number of active enterprises
in Russia; (ii) number of growing enterprises per
thousand people living in each region; (iii) number
of declining enterprises per thousand people living
in each region; (iv) ratio of the number growing and
declining enterprises for each region.
Also, study included testing of following four
hypotheses: (i) how growing and fading enterprises
in Russia appear relatively and rarely; (ii) values
of four indicators under consideration have a
of the country; (iii) in most regions number of
growing enterprises exceeds number of declining
enterprises; (iv) the territorial location of the
maximum and minimum values for each indicator.
Made evaluation using economic and
mathematical modeling for each indicator, the
normal distribution functions were used. In
Pinkovetskaia (2020) and Pinkovetskaia and
Slepova (2018), are presents methodological
approach to their development and use to determine
as well as the ranges of variation of values for most
regions. Note that such functions provide unbiased
characteristics of the studied regularities. In the
work, determined the regions with maximum and
minimum values of indicators.
Results
number of active enterprises in Russia in 2020 was
2821827 units. From these 95962 enterprises were
considered to be growing and 83295 enterprises
were considered to be declining. The share of
growing enterprises in the total number of active
enterprises in 2020 was 3.40 %. That is, every
twenty-ninth enterprise belongs to the growing
ones. The share of declining enterprises in the total
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Revista Perspectiva Empresarial, Vol. 9, No. 1, enero-junio de 2022, 23-31
ISSN 2389-8186, E-ISSN 2389-8194
number of active enterprises is 2.95 %. Accordingly,
dying one. Results show that both growing and
declining enterprises in Russia appear relatively
It should be noted that share of enterprises
number of employees is slightly higher than that
decrease in their number. In general, in absolute
majority (93.65 %) of enterprises in Russia in 2020,
number of employees.
In the course of computational experiment,
economic and mathematical modeling was
carried out on the basis of empirical data. Models
that describe distribution of four indicators that
characterize the relative number of enterprises with
of employees in all 82 regions of Russia in 2020 are
shown below:
(i) number of growing enterprises per thousand
people living in each region:
(ii) Number of declining enterprises per
thousand people living in each region:
(iii) Ratio of the number of growing and
declining enterprises for each region:
in the testing process according to Shapiro-Wilk,
Pearson and Kolmogorov-Smirnov criteria.
At the next stage of study, patterns were
indicators under consideration by region, shown
in Table 1. Column 2 shows data describing the
average values of indicators. Ranges in which the
values of indicators for most regions are located
show in the third column of the table.
Table 1. Characteristics of enterprises with a signicant increase and decrease in the number of employees
Indicator Average values Values for most regions
Number of growing enterprises per thousand people living in each region 0.56 0.26-0.86
Number of fading enterprises per thousand people living in each region 0.52 0.25-0.79
Ratio of the number of growing and fading enterprises for each region 1.10 0.74-1.46
Source: author own elaboration.
Average number of growing enterprises per
thousand people, reached less than 0.56 in 2020.
The lowest value was observed in the Krasnodar
region (0.05) and the highest in the Sakha republic
(3.57). In most regions, this indicator did not exceed
0.86. Average number of declining businesses per
thousand people was 0.52 in 2020. It is interesting to
note that the lowest value was also in the Krasnodar
region (0.05) and the highest in the Sakha republic
(3.56). In most regions, value of this indicator did
not exceed 0.79.
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Discussion
Average value of the ratio between the
number of growing and declining enterprises
in the Russian regions was 1.10. The trend of
exceeding the values for growing enterprises was
observed in 2020 in 49 regions: cities Moscow;
St. Petersburg; Sevastopol; republics Tyva,
Crimea, Tatarstan, Karelia, Udmurtia, Chuvashia,
Kalmykia, Buryatia, Arkhangelsk, Murmansk,
Chelyabinsk, Voronezh, Ulyanovsk, Belgorod,
Kursk, Kemerovo, Vologda, Novosibirsk, Saratov,
Tver, Kaluga, Sverdlovsk, Penza, Amur, Oryol,
Moscow, Tomsk, Tyumen, Kostroma, Volgograd,
Leningrad, Ivanovo, Tula, Astrakhan, Magadan,
Lipetsk, Bryansk, Nizhny Novgorod, Rostov,
Novgorod Regions, Khabarovsk, Primorsky, Perm;
Krasnoyarsk territories; Jewish Autonomous
region; Chukotka Autonomous district. In two
regions, Yaroslavl region and Sakha republic, the
values of indicators for growing and declining
enterprises were equal. In 31 regions, is have
tendency to exceed the values for declining
enterprises compared to growing enterprises.
These included: republics Dagestan; North
Ossetia-Alania; Ingushetia; Karachay-Cherkessia;
Kabardino-Balkaria; Chechen; Khakassia; Komi;
Altai; Mordovia; Mari El; Bashkortostan; Adygea;
Tambov; Kurgan; Pskov; Omsk; Orenburg;
Irkutsk; Vladimir; Kaliningrad; Ryazan; Sakhalin;
Smolensk; Kirov; Samara regions; Zabaykalsky;
Altai; Kamchatka; Krasnodar; Stavropol
territories. Thus, can conclude that the third
hypothesis has been confirmed.
To test the second hypothesis that values of
differentiation by region, an analysis of the scope
variation of each indicator presented in Table 1 was
the mean square deviations to the average values of
the second indicator, 52 %; for the third indicator,
differentiation in the considered regions of the
values for each indicator. Therefore, the second
maximum and minimum values of each indicator.
At the same time, maximum and minimum values
are those that correspondingly exceed the upper
limits of the ranges shown in the third column of
Table 1 and are smaller than the lower limits of the
ranges. Results of this analysis are shown in Table
2. Along with the lists of regions, this table also
shows territorial location of the regions by federal
districts.
Table 2. Regions with maximum and minimum values of indicators
Indicator Maximum values Minimum values
Number of growing enterprises
per thousand people living in
each region
Perm region, republic Buryatia, Magadan
region, Novgorod region, Volgograd region,
Astrakhan region, republic Crimea, cities
Moscow and Saint Petersburg, Tomsk region,
republic Sakha (Yakutia).
Located in the Volga and Central Federal
Districts have one region each, the Southern
Federal District has three regions and the Far
Eastern, Northwestern and Siberian Federal
Districts have two regions each.
Krasnodar territory, Altai territory, Chechen
republic, republic Khakassia, republic
Dagestan, Irkutsk Region, republic North
Ossetia-Alania, Tambov region, Karachay-
Cherkess republic, Stavropol territory.
They are located in the North Caucasus
Federal District (ve regions), the Southern
and Central Federal Districts (one region
each) and the Siberian Federal District
(three regions).
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Indicator Maximum values Minimum values
Number of declining enterprises
per thousand people living in
each region
Astrakhan region, republic Tyva, Kaliningrad
region, Volgograd region, republic Crimea,
cities Saint Petersburg and Moscow, Tomsk
region, republic Sakha (Yakutia).
They are located in the Southern Federal District
(three regions), the North-Western Federal
District (two regions), the Central, Siberian and
Far Eastern Federal Districts (one region each).
Krasnodar territory, Altai territory, Rostov
region, Irkutsk region, republic Khakassia,
Chechen republic, republic of Kalmykia.
Located in the North Caucasus Federal
District (one region),
the Southern and Siberian Federal districts
(three regions each).
Ratio between number
of growing and declining
enterprises for each region
Astrakhan region, Magadan region, republic
Buryatia, Lipetsk region, Bryansk region,
Nizhny Novgorod region, city Saint Petersburg,
Rostov region, Sevastopol, Novgorod region.
They are located in the Southern Federal District
(three regions), the North-Western and Central
Federal Districts (two regions each) and the Far
Eastern, Volga, and Siberian Federal Districts
(one region each).
Dagestan republic, republic North Ossetia-
Alania, Tambov region, republic Ingushetia,
Karachay-Cherkess republic, Kabardino-
Balkar republic, Chechen Republic,
republic Khakassia, Trans-Baikal territory.
They are located in the North Caucasus
Federal District (six regions), the Far
Eastern, Central and Siberian Federal
Districts (one region each).
Source: author own elaboration.
Analysis showed that there is no connection
between the territorial location of regions and
maximum (minimum) values of the indicators.
That is, regions with both high and low values of
indicators are located in different federal districts.
Conclusions
novelty, include the following: methodological
approach is proposed to evaluate the values
of indicators that characterize the number of
growing and declining enterprises per thousand
inhabitants in the Russian regions; developed
economic and mathematical models that describe
current distribution of the indicators values that
characterize the number of growing and declining
enterprises per thousand inhabitants, as well as the
ratio of these indicators by region; proved that in
the absolute majority of enterprises there was no
employees; shown that the shares of both growing
and declining enterprises in the total number of
active enterprises are small (about 3 %); shown
that the average value of the ratio between number
of growing and declining enterprises in the Russian
regions was 1.10; proved that in most regions
the number of growing enterprises exceeds the
number of declining ones, however, in a number
of regions the opposite trend is observed; average
values of the number of growing and declining
enterprises per thousand inhabitants in the regions
were determined, which amounted to 0.56 and
0.52, respectively; shown that the values of four
differentiation in the regions of the country;
shown that the territorial location of the country’s
minimum values for each of the four indicators.
The obtained results are of theoretical and
on the demography of enterprises. Namely, when
monitoring the share of growing and declining
enterprises in the Russian regions. The results
of work can be applied in the current activities of
state structures and public organizations, when
justifying measures to support enterprises that
are characterized by an increase in the number of
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ISSN 2389-8186, E-ISSN 2389-8194
employees. In addition, the information obtained
can be used to solve problems of increasing the
share of growing enterprises in regions where such
enterprises are not widely developed. Results of the
work are of interest to banks and credit institutions.
New knowledge related to the regional
characteristics of activities growing and
declining enterprises can be used in the training
of undergraduate and graduate students at
universities. Further studies can be conducted to
assess the industry characteristics of enterprises
with high rates of employee numbers. In the course
of research, there were no restrictions on empirical
data, since information was considered for all 82
regions of Russia.
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