CC BY
0SUSTAINABLE DEVELOPMENT AND ENGINEERING ECONOMICS 1, 2024
Research article
DOI: https://doi.org/10.48554/SDEE.2024.1.2
Study of the Factors Relevant to the Management Model for Developing Russia’s
Regional Socio-Economic Systems
Pavel Karpenko*1, Natalya Viktorova1 , Hoang Hieu Tran2
1
Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation,
karpenko_pavel@mail.ru, viktorova_ng@spbstu.ru
2
University of Da Nang, Da Nang, Vietnam, hieuth.due@gmail.com
*
Corresponding author: karpenko_pavel@mail.ru
Abstract
T
he Russian economic space is characterised by a significant differentiation in the levels of socio-
economic development of the country’s various regions, which manifests itself in natural, territorial,
socio-cultural, economic, political and other aspects. The results of socio-economic differentiation
are unique regional socio-economic systems, which necessitates the formation of individual approaches
to managing their development. Therefore, management decisions made at the federal centre, as well
as by regional authorities, affect the activities of economic entities in the regions and the population’s
level of well-being in different ways. Social security is an integral element of the high quality of life
of the population and is largely the basis for improving the economic status of the region, increasing
the value of human capital. Thus, it is necessary to develop methods and tools for ensuring the social
safe development of regional socio-economic systems, considering the specific characteristics of each
region. From these perspectives, we can discuss the stability and social performance of the regional
economy. Despite a broad scientific background, the factors contributing to the development and the
results of regional socio-economic systems, considering the need for social security, have not been
examined. The present research aims to fill this gap by developing a management model for the social
and safe development of Russia’s regions, using the city of St Petersburg as the case study.
Keywords: management model for regional development, tone of news flow, resource classification principles,
management factors’ impacts, regional social security, regional economy’s stability
Citation: Karpenko, P., Viktorova, N., Tran, H.H., 2024. Study of the Factors Relevant to the Management
Model for Developing Russia’s Regional Socio-Economic Systems. Sustainable Development and Engineering
Economics 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
© This work is licensed under a CC BY-NC 4.0
Karpenko, P., Viktorova, N., Tran, H.H., 2024. Published by Peter the Great St. Petersburg Polytechnic University
28 Enterprises and sustainable development of regions
SUSTAINABLE DEVELOPMENT AND ENGINEERING ECONOMICS 1, 2024
Научная статья
УДК 330.4
DOI: https://doi.org/10.48554/SDEE.2024.1.2
Исследование Факторов Модели Управления Социально-Безопасным
Развитием Региона
Павел Карпенко1*, Наталья Викторова1 , Хоанг Хиеу Чан2
1
Санкт-Петербургский политехнический университет Петра Великого, Санкт-Петербург, Россия,
karpenko_pavel@mail.ru, viktorova_ng@spbstu.ru
2
Данангский университет, Дананг, Вьетнам, hieuth.due@gmail.com
*
Автор, ответственный за переписку: karpenko_pavel@mail.ru
Аннотация
Д
ля российского экономического пространства характерна значительная дифференциация
уровней социально-экономического развития различных регионов, проявляющаяся
как в природном, территориальном, так и в социокультурном, экономическом,
политическом и ином аспектах. Результатами социально-экономической дифференциации
становятся уникальные региональные социально-экономические системы, что обуславливает
необходимость формирования индивидуальных подходов к управлению их развитием. Поэтому
управленческие решения, генерируемые федеральным центром, а также региональными органами
власти, неодинаково сказываются на деятельности хозяйствующих субъектов региона и уровне
благосостояния населения. Социальная безопасность является составным элементом высокого
качества жизни населения, более того, социальная безопасность во многом является базисом
для повышения экономического статуса региона, роста стоимости человеческого капитала.
Вследствие этого необходима разработка методов и инструментов обеспечения социально
безопасного развития региональных социально-экономических систем с учётом специфики
регионов. Именно с этих позиций можно говорить об устойчивости региональной экономики
и о её социальной результативности. Целью данного исследования является разработка модели
управления социально-безопасного развития региона на примере города Санкт-Петербург.
Исследовательский разрыв заключается в том, что несмотря на достаточно широкий научный
задел, существует явный научный пробел в определении факторов и результатов развития
региональных социально-экономических систем с учётом необходимости обеспечения
социальной безопасности.
Ключевые слова: модель управления социально-безопасным развитием региона, тональный окрас
новостного потока, принципы классификации ресурсов, воздействие факторов, социальная безопасность
региона, устойчивость региональной экономики.
Цитирование: Карпенко, П., Викторова, Н., Чан, Х.Х., 2024. Исследование Факторов Модели Управле-
ния Социально-Безопасным Развитием Региона. Sustainable Development and Engineering Economics 1, 2.
https://doi.org/10.48554/SDEE.2024.1.2
Эта работа распространяется под лицензией CC BY-NC 4.0
© Карпенко, П., Викторова, Н., Чан, Х.Х., 2024. Издатель: Санкт-Петербургский политехнический
университет Петра Великого
Предприятия и устойчивое развитие регионов 29
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
1. Introduction
The competitiveness of a national economy is determined by the distinct capabilities of regional
socio-economic systems, considered as local centres for generating benefits, in connection with which
the choice of directions for regional development becomes critical. The main goal of the development
of regional and national socio-economic systems is to improve the population’s quality of life, based on
stable economic growth and compliance with environmental restrictions. The Russian economic space
is characterised by a significant differentiation in the levels of socio-economic development of the coun-
try’s various regions, which manifests itself in natural, territorial, socio-cultural, economic, political
and other aspects. The results of socio-economic differentiation are unique regional socio-economic
systems, necessitating the formation of individual approaches to managing their development. Thus,
the purpose of this study is to develop a management model for the social and safe development of the
regions, based on the example of the city of St Petersburg.
Despite a fairly broad scientific background, determining the factors contributing to the develop-
ment and the results of regional socio-economic systems, considering the need to ensure social security,
remains a research gap. Significant differences in the results of the managerial influences of the federal
centre and the regions on regional socio-economic development reveal the need for additional research
in this area.
2. Literature Review
To form a conceptual model for ensuring the socially safe management of the development of re-
gional socio-economic systems, it is necessary to identify the factor specificity. One of the key signs of
differentiation can be the principle of classifying economic resources. The most complete classification
of economic resources as factors influencing the development of regional socio-economic systems is
presented in a previous study (Kisurkin, 2012). The author identifies five main groups – natural, labour,
financial, entrepreneurial and knowledge factors. Each of the presented groups of factors can act as the
core of the model for managing the development of a regional socio-economic system.
A graphic systematisation and brief descriptions are shown in Figure 1.
Figure 1. Systematisation of economic factors
30 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
However, taking into account this study’s purpose to improve the tools for the socially safe devel-
opment of regional socio-economic systems, instead of labour factors, the model will consider human
factors as the group that fully covers all human resources and human potential located in the territory of
a particular region. Through the reactions of human resources, people can most fully assess how socially
safe their region of residence is and use this effect in strategic regional planning.
Using the state of human resources as the core of the model being developed involves the forma-
tion of a system of input impact factors and a system of input conversion results. The system of input
impact factors should be understood as a set of quantifiable variables that are exogenous in relation to
the state of human resources. At the same time, it should be noted that being fully or partially controlla-
ble is an invariably obligatory property of these factors. It is expedient to make these factors distinct in
accordance with the specifics of the differentiation of economic resources described earlier. Thus, in the
first place, natural factors can be distinguished. As a manageable indicator that characterises the impact
of management entities on the development of a set of natural factors influencing the regional socio-eco-
nomic system, an investment in a fixed asset aimed at protecting the environment and the rational use
of natural resources can be singled out. This indicator is differentiated in accordance with the areas of
investment, namely investments in the protection of atmospheric air, the protection and rational use of
water resources, as well as the construction and maintenance of wastewater treatment plants. The select-
ed set of investment areas is not exhaustive; however, these areas comprise the majority of the totality.
The increment of these parameters in the medium and long terms has an impact on improving the level
of environmental safety of a specific region, which in turn has a positive effect on the overall average
state of the physical and moral health of the population. The presented formal–logical connection deter-
mines the conversion of the process of incremental investments in fixed assets aimed at environmental
protection and rational use of natural resources into a change in the state of human resources, which in
turn can potentially affect the overall development of the regional socio-economic system. In addition
to the selected investment indicator, which invariably has a positive impact on the state of human re-
sources, it is necessary to highlight indicators that reflect the negative impact on the natural resources of
a region. The necessary condition of full or partial controllability determines the technogenic nature of
these indicators. Thus, the most appropriate indicator in this case is the volume of emissions of harmful
(polluting) substances. This indicator is multidimensionally manageable, which is determined by the
possibility of reducing the volume of manufacturing products, the technological process of production,
accompanied by significant emissions of pollutants, and the possibility of compensating for this impact
by improving the systems for cleaning and making up for emitted pollutants. The impact of changes in
this indicator on the state of human resources is reversible, which determines the need to reduce it. The
combination of the above indicators is necessary and sufficient for describing natural factors’ impact
on human resources in the framework of the development of a regional socio-economic system. Other
natural factors are neither fully nor partially controllable, forming the basis for an exclusive evaluation
model that is unsuitable for managing the development of regional socio-economic systems.
Next, it is necessary to consider a set of factors that multidimensionally describe the state of ma-
terial resources that form both internal and external environments. This set can be conditionally divided
into production factors and infrastructure factors. The essence of production factors is determined by
the state of the material resources used in the process of generating wealth. This set of resources can
be divided in accordance with the sign of turnover, as well as with the nature of the participation in the
production process. The general comparative state of fixed production assets can be described by the
indicator of the use of production capacities. It may also be conditionally expedient to use the value of
accumulated depreciation as the analysed indicator of the input influence. However, this indicator has
significant industry specifics, which determines the need for an industry specification of the model, in
turn contradicting the goal set in this study. The indicator of production capacity utilisation is measured
as a percentage, essentially reflecting the share of the actively used production potential of the region
under study. This indicator is exclusively manageable and can be largely regulated by the subjects of
management of the regional socio-economic system, both directly, by placing a state order, and indirect-
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 31
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
ly, by setting special conditions for the functioning of regional enterprises. The increase in this indicator
has a direct impact on the state of human resources, primarily due to the regional labour market satu-
ration with supply and the decrease in social tension in this regard, as well as the creation of a socially
safe environment. The GRP per capita should also be considered as a complex factor of production. This
indicator is dualistic in nature, and in many respects is the result. However, in modern conditions of the
development of regional socio-economic systems, the complex result, which is directly the GRP per cap-
ita, is determined not so much by the conditional efficiency of able-bodied human resources, as by the
efficiency, adaptability and predictability of the process of its formation, at both the technological and
administrative levels. At the same time, it is the GRP per capita that essentially reflects the population’s
level of well-being, which in turn directly affects the state of human resources. Thus, the GRP per capita
is the most appropriate factor to use as an indicator of the input impact.
In parallel with the development of the production environment, the integrated development of
regional socio-economic systems invariably involves the development of infrastructure as a connecting
inter-production resource. The degradation and unsatisfactory state of the regional infrastructure deter-
mine the increase in logistics costs, in turn leading to greater complexity of the interaction between the
population and the business in both the production process and the consumption process. Among the
indicators reflecting the state of infrastructure factors, it is most appropriate to single out the indicator
of the availability of road transport, differentiated into public (in particular, buses, representing the most
versatile type of public transport) and private (in particular, cars). This indicator can also be supplement-
ed by an indicator of the length of public roads.
The presented set of input influence factors can potentially be supplemented by a set of indicators
reflecting the state of the healthcare system, education and other social indicators. As part of this study,
among the indicators reflecting the state of the social environment, it was decided that the following
would be used: the number of students in general education institutions receiving meal subsidies, the
ratio of healthcare institutions using the internet to the total number of healthcare institutions, as well
as real accrued wages as a percentage of those earned in the corresponding period in the previous year.
Next, it is necessary to consider the totality of the resulting indicators in relation to the human
resources. Such an environment is manifested in a set of indicators reflecting the level of social security,
such as the number of offences in the context of the main articles of the Criminal Code of the Russian
Federation, as well as in a set of indicators reflecting the conditional “improvement” of society, such as
the volume of consumed alcoholic beverages and drugs.
It is also essential to separately note the increase in the unemployment rate as a result of the re-
verse conversion of the increment in the main indicators of input influence. The totality of the resulting
indicators is presented in Table 2.
The above set of indicators can be aggregated in a single conceptual model (Figure 2).
32 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
Figure 2. Conceptual model for managing the development of regional socio-economic systems (Rodi-
onov et al., 2021)
As shown in Figure 2, the core of the conceptual model for managing the socially safe develop-
ment of regional socio-economic systems is the set of quantifiers of the state of human resources. These
quantifiers can be aggregated, based on the analysis of the comparative state of the communicative
manifestations of a region’s population. Such a thesis assumes that the psychological state of the repre-
sentatives of society relates to the results of their professional activities and other social manifestations.
The state of human resources can be differentiated in accordance with a variety of classification
features (Kulibanova, Teor, 2018; Kulibanova, 2018); however, the most appropriate one in this study is
the allocation of social (Karpenko et al., 2018) and emotional characteristics of human resources. Two
of the key properties of the process of forming these characteristics are consistency and duration, which
determine the need to consider the significant time lag in the conversion of managerial impact, which
theoretically takes several years.
Development requires a methodology for assessing the emotional characteristics of human re-
sources, effectively reflecting the state of such resources. The key properties of primary information in
the framework of the analysis are objectivity, relevance and universality.
As a rule, the key emotional (tonal) characteristics of natural information, include positivity, neg-
ativity and neutrality. These tonal characteristics can be called primary. The assessment of these param-
eters in relation to the information flow of the regional socio-economic system can be differentiated by
the following indicators:
Tcneut
i
– the level of neutral sentiment of information unit i, which describes the state of the region-
al socio-economic system
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 33
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
Tcipos – the level of positive sentiment of information unit i, which describes the state of the re-
gional socio-economic system
Tcneg
i
– the level of negative sentiment of information unit i, which describes the state of the re-
gional socio-economic system
neut
Tcom i
– the level of neutral tone of information unit i, which describes the human resources’ reac-
tion to the state of the regional socio-economic system
pos
Tcomi
– the level of positive sentiment of information unit i, which describes the human resources’
reaction to the state of the regional socio-economic system
neg
Tcom i
– the level of negative sentiment of information unit i, which describes the human resources’
reaction to the state of the regional socio-economic system
The presented set of indicators, based solely on the analysis of primary information, may not fully
reflect the dynamic changes in the state of human resources. An addition to this parameter is the general
level of emotionality of the information unit, equal to the ratio of the sum of the levels of positive and
negative sentiments to the level of the neutral sentiment of the information unit. The mathematical inter-
pretation of these indicators is represented by formulas 1–4.
dis
Tc pos dis
pos
Tcom
T
c = (1) T comi = i
(3)
Tcneg neg
Tcom i
Tcifull
=
(T pos
ci + Tcneg
i
) (2) T full
=
(T pos
comi
neg
+ Tcom i
) (4)
neut comi neut
T ci T comi
with the following definitions:
Tcdis
i
– the level of the tonal gap of information unit i, which describes the state of the regional
socio-economic system
dis
Tcom i
– the level of the tonal gap of information unit i, which describes the human resources’ re-
action to the state of the regional socio-economic system
Tcifull – the general level of emotionality of information unit i, which describes the state of the
regional socio-economic system
full
Tcom i
– the general level of emotionality of information unit i, which describes the human resourc-
es’ reaction to the state of the regional socio-economic system
The above set of indicators allows us to describe the tonal colour as a general news flow and a reac-
tive information flow. The key characteristic reflecting the state of human resources is the ratio of these
tonal characteristics, which determines the tonal gap. The mathematical interpretation of these indicators
is represented by formulas 5–9:
(T )
2
Dineut
= neut
ci
neut
− Tcom (5)
i
34 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
(T )
2
Dipos
= pos
ci
pos
− Tcomi
(6)
(T )
2
Dineg
= neg neg
− Tcom (7)
ci i
2
Tcipos Tcom
pos
Didis
= neg − negi (8)
Tc Tcomi
i
( ) ( )
2
Tc pos + Tcneg pos
Tcom neg
+ Tcom
=Di full i
neut
i
− i
neut
i
(9)
Tci Tcomi
with the following definitions:
Dineut– a break in the level of the neutral tone of information unit i, which describes the state of
the regional socio-economic system and the reactive information units in relation to it
Dipos – a gap in the level of positive sentiment of information unit i, which describes the state of
the regional socio-economic system and the reactive information units in relation to it
Dineg– a gap in the level of negative sentiment of information unit i, which describes the state of
the regional socio-economic system and the reactive information units in relation to it
Didis
– a gap in the tone of information unit i, which describes the state of the regional socio-eco-
nomic system and the reactive information units in relation to it
Di full
– a gap in the general level of emotionality of information unit i, which describes the state
of the regional socio-economic system and the reactive information units in relation to it
The literature review is based on the materials presented by the cited authors (Karpenko et al.,
2018; Rodionov et al., 2021).
3. Methods and Materials
The above technique can be automated using the Python programming language. At the initial
stage of the presented methodology, both the information describing the state of the regional socio-eco-
nomic system and the reactive information in relation to it are searched and aggregated. As part of the
implementation of this algorithm, it is advisable to use the social network VKontakte. This choice is
primarily due to the breadth of coverage of the population, which is on average 90% at the regional lev-
el. To test the developed methodology, the city of federal significance, St Petersburg, was chosen as the
case study. One of the most dynamic and widespread concentrators of news information of the regional
socio-economic system in the case of St Petersburg is the Vesti St Petersburg community. As an officially
registered mass media, this community exclusively contains news information of regional importance
and targets the most communicatively active audience.
The Dostoevsky instrumental library was chosen for the purpose of assessing the sentiments of
both news information and reactive information. Based on the results of assessing the primary charac-
teristics of the tonality of the information units, the previously presented characteristics of the tonal gap,
which directly characterise the state of human resources, are calculated and aggregated.
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 35
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
In accordance with the previously presented conceptual model for managing the development of
regional socio-economic systems, its core determines the conversion of the set of quantifiers of the state
of human resources, expressed by the tonal gap of the information environment. The average dynamics
of the primary indicators of the tonal gap are formally logically justified, which indirectly confirms the
feasibility of the mathematical formalisation of the built conceptual model through the classical meth-
odology of regression analysis.
The regression quality criteria applied in this work are defined as follows:
- the significance of the models is assessed using Fisher’s F-test. In the framework of this study,
the limit value of this criterion is taken to be 0.1 or 10%;
- the quality of the model is determined primarily by the volume of the explained variance of the
endogenous variable, as indicated by the coefficient of determination (R2);
- the level of significance of the relation between the endogenous variable and the exogenous vari-
ables included in the model is determined by the p-level of significance of each variable. In the multiple
regression equations, the specificity of the sample described above determines a potentially sufficiently
high p-level of significance for the studied regressors. Therefore, compared with Fisher’s F-test, a sig-
nificantly more significant threshold is determined for this indicator, up to 0.2 or 20%. The backward
method is used as an optimisation method in this study;
- the applied quality of describing the variance of an endogenous variable by the variance of exog-
enous variables is determined by the average approximation error, standard deviation, characteristics of
structural outliers and structural gaps, among many others;
- the most significant binary quality criterion of a regression model is the rationale for the direction
of the impact of an exogenous variable on an endogenous one.
4. Results and Discussion
Let us consider the impact of natural factors on the gap in the level of the positive tone in a region-
al socio-economic system’s information environment. Based on the results of the primary analysis and
optimisation, the following regression equation is obtained (formula 10):
−0, 037 + 0, 0004* N1i + (1,3 − 06 ) * N 3i
Dipos = (10)
In the framework of the resulting equation, the p-significance level of all regressors corresponds
to the established criterion. The value obtained from Fisher’s F-test is 0.0018, indicating the high sig-
nificance of the resulting regression equation. The coefficient of determination of this equation is 0.955,
from which it can be concluded that the variance of the “volume of emissions of harmful (pollutant)
substances into the atmospheric air from road transport” and the variance of “investments in fixed assets
aimed at protecting the environment and rational use of natural resources (protection and rational use of
water resources)” explain about 96% of the dispersion of the gap in the level of positive sentiment in the
regional socio-economic system’s information environment. Of course, a significant part of the unifor-
mity of variances is determined by systemic changes; however, even taking into account possible errors,
this value indicates the high quality of the generated regression equation. To assess the applied quality
of the model, we should compare the theoretical and actual values of the endogenous variable, as well as
the boundaries of the acceptable interval (Figure 3).
36 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
Figure 3. Dynamics of actual and theoretical values of
the gap in the level of positive sentiment
in a regional socio-economic system’s information environment, depending on natural factors (Karpen-
ko, 2021)
As shown in the graph (Figure 3), the overall dynamics of the actual and theoretical values of the
gap in the level of positive tonality in a regional socio-economic system’s information environment are
comparable, indicating the high quality of the generated regression equation. Of course, an insignificant
structural outlier appears in 2015, primarily due to the insignificant value of the standard deviation be-
cause of which the boundaries of the permissible interval are extremely strict. Due to this specificity, the
corresponding structural outlier can be ignored.
The above equation determines the direct nature of the impact of the “volume of emissions of
harmful (pollutant) substances into the atmospheric air from road transport” and “investments in fixed
assets aimed at protecting the environment and rational use of natural resources (protection and rational
use of water resources)” on the gap in the level of the positive tone in a regional socio-economic system’s
information environment. Regarding the first factor, a formal–logical connection is observed, while the
impact of the second factor shows a contradictory nature. This impact can be substantiated by a potential
lag in the impact on the specifics of the use of water resources. Consequently, from the management
perspective, the “volume of emissions of harmful (polluting) substances into the air from road transport”
is primary (indicator N1). The coefficient of elasticity of this indicator is 1.008%.
Let us consider the impact of production factors on the gap in the level of positive tonality in the
regional socio-economic system’s information environment. Based on the results of the primary analysis
and optimisation, the following regression equation is obtained (formula 11):
Dipos 2, 269 − 0, 021* P2i
= (11)
In the framework of the resulting equation, the p-significance level of the residual regressor corre-
sponds to the established criterion. The value obtained from Fisher’s F-test is 0.07, indicating a sufficient
significance of the resulting regression equation. The coefficient of determination of this equation is 0.5,
from which it can be concluded that the dispersion of “GRP per capita” explains about 50% of the dis-
persion of the gap in the level of positive sentiment in the regional socio-economic system’s information
environment. This value is insufficient to interpret the model as having high quality but enough to accept
the model. For a paired regression model with macrospecificity, such value is acceptable for further re-
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 37
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
search. To assess the applied quality of the model, the theoretical and actual values of the endogenous
variable, the boundaries of the acceptable interval, are compared (Figure 4).
Figure 4. Dynamics of actual and theoretical values of
the gap in the level of positive sentiment
in a regional socio-economic system’s information environment, depending on production factors
(Karpenko, 2021)
As shown in the graph (Figure 4), the overall dynamics of the actual and theoretical values of the
gap in the level of positive tonality in the regional socio-economic system’s information environment
are comparable, indicating the sufficient quality of the generated regression equation. However, struc-
tural gaps are observed in 2016 and 2020. This specificity is due, first of all, to significant non-economic
shocks in these periods, particularly the COVID-19 pandemic. Due to this specificity, the corresponding
structural outliers can be ignored.
The given equation of pair regression (formula 11) reflects the reverse effect of the change in the
“GRP per capita” on the gap in the level of positive tonality in the regional socio-economic system’s
information environment, which in turn is formally and logically substantiated. At the same time, the
coefficient of elasticity of this indicator is -16.6%, indicating an extremely strong influence of produc-
tion specifics on the change in the gap in the level of positive sentiment. Thus, this indicator is primary
in terms of managing the development of the regional socio-economic system.
Let us consider the impact of infrastructural factors on the gap in the level of positive sentiment
in the regional socio-economic system’s information environment. Based on the results of the primary
analysis and optimisation, the following regression equation is obtained (formula 12):
Dipos 0,589 − 0, 00013* I 3i
= (12)
In the framework of the resulting equation, the p-significance level of the residual regressor cor-
responds to the established criterion. The value obtained from Fisher’s F-test is 0.14, indicating the in-
sufficient significance of the obtained regression equation. This fact determines the need to exclude this
model from the previously formulated conceptual equation. However, the coefficient of determination
of this equation is only 0.32, which indicates the relative secondary nature of factor I3, “length of public
roads”. Moreover, the relation is inverse, which is not logically interpreted. Thus, it can be established
that infrastructural factors have no significant impact on the gap in the level of positive sentiment in
the regional socio-economic system’s information environment. This fact may be due to the extreme
differentiation of the infrastructural conditions of the regions, as well as the human resources’ relative
38 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
adaptation to these conditions.
In conclusion, it is necessary to consider the impact of social factors on the gap in the level of the
positive tone in the regional socio-economic system’s information environment. Based on the results of
the primary analysis and optimisation, the following regression equation is obtained (formula 13):
Dipos =
−3,54 + 0, 038* S 2i − 0, 0007 * S3i (13)
In the framework of the resulting equation, the p-significance level of the residual regressor corre-
sponds to the established criterion. The value obtained from Fisher’s F-test is 0.017, indicating the suffi-
cient significance of the obtained regression equation. The coefficient of determination of this equation
is 0.71, from which it can be concluded that the variance of the “ratio of healthcare institutions using
the internet to the total number of healthcare institutions” and the variance of “real accrued wages as a
percentage of those earned in the corresponding period in the previous year” explain about 71% of the
variance of the gap in the level of positive tonality in the regional socio-economic system’s information
environment. This value is necessary and sufficient for the interpretation of the model as having high
quality. To assess the applied quality of the model, we should compare the theoretical and actual values
of the endogenous variable, as well as the boundaries of the acceptable interval (Figure 5).
Figure 5. Dynamics of actual and theoretical values of
the gap in the level of positive sentiment in
the regional socio-economic system’s information environment, depending on social factors (Karpen-
ko, 2021)
As shown in Figure 5, the overall dynamics of the actual and theoretical values of the gap in the
level of positive tonality in the regional socio-economic system’s information environment are compa-
rable, indicating the sufficient quality of the generated regression equation. However, a structural gap
appears in 2014. This specificity is due, first of all, to economic shocks caused by fluctuations in the
exchange rate of the national currency. Due to this specificity, the corresponding structural outlier can
be ignored.
The above regression equation reflects the reverse effect of the change in “real accrued wages as
a percentage of those earned in the corresponding period in the previous year” on the gap in the level
of positive sentiment in the regional socio-economic system’s information environment, which in turn
is formally and logically substantiated. However, the direct impact of the change in the “ratio of health-
care institutions using the internet to the total number of healthcare institutions” determines the need to
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 39
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
exclude it from further analysis. Thus, in this case, indicator S3, “real accrued wages as a percentage of
those earned in the corresponding period in the previous year”, is decisive. At the same time, the coeffi-
cient of elasticity of this indicator is -0.52%. Based on the results of the regression analysis, infrastruc-
tural factors, as well as some natural, industrial and social factors, can be completely excluded.
Next, it is necessary to consider the resulting part of the conceptual model, which describes the
impact of the core (the state of human resources) on the set of resulting indicators. The system of criteria
described earlier is also preserved for these paired regression equations. First, we consider the impact of
changing the gap in the level of positive sentiment in the regional socio-economic system’s information
environment on indicator R1, “the number of crimes (murder) registered in the reporting period under
Art. 105 of the Criminal Code of the Russian Federation”. Based on the results of the analysis, the fol-
lowing regression equation is obtained (formula 14):
R1i 75, 6 + 930, 7 * Dipos
= (14)
The value obtained from Fisher’s F-test is 0.05, indicating the model’s sufficient level of signifi-
cance. However, the coefficient of determination is 0.49, which explains less than 50% of the variance
of the endogenous variable. Since only a pairwise regression model is considered, it can be assumed that
this level is sufficient in an isolated form. A comparison of the dynamics of the actual and theoretical
values of
the endogenous variable confirms this thesis.
As shown in Figure 6, the actual dynamics of the number of crimes (murder|) registered in the
reporting period under Art. 105 of the Criminal Code of the Russian Federation are sufficiently different
from the theoretical one. Thus, it can be argued that the management of this indicator through the admin-
istration of the information environment is mathematically possible but not effective enough.
Figure 6. Dynamics of actual and theoretical values of
the number of crimes (murder) registered under
Art. 105 of the Criminal Code of the Russian Federation, depending on the gap in the level of positive
sentiment in the regional socio-economic system’s information environment (Karpenko, 2021)
The use of this approach to management is expedient only in combination with other, more effec-
tive tools. The coefficient of elasticity in this case is 0.62%, which is logically justified.
Next, we consider the impact of changing the gap in the level of positive tonality in the regional
socio-economic system’s information environment on indicator R2, “the number of crimes (intentional
40 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
infliction of harm to health) registered in the reporting period under Art. 111 of the Criminal Code of the
Russian Federation”. Based on the results of the analysis, the following regression equation is obtained
(formula 15):
R2i 257, 7 + 1434,5* Dipos
= (15)
The value obtained from Fisher’s F-test is 0.08, indicating the model’s sufficient level of signif-
icance. However, in this case, the coefficient of determination is 0.41, which explains only 41% of the
variance of the endogenous variable. A comparison of the dynamics of the actual and theoretical values
of the endogenous variable is shown in Figure 7.
Figure 7. Dynamics of actual and theoretical values of the number of crimes (intentional infliction of
harm to health) registered under Art. 111 of the Criminal Code of the Russian Federation, depending
on the gap in the level of positive sentiment in the regional socio-economic system’s information envi-
ronment (Karpenko, 2021)
As illustrated in Figure 7, the actual dynamics of the number of crimes (intentional infliction of
harm to health) registered in the reporting period under Art. 111 of the Criminal Code of the Russian
Federation sufficiently differ from the theoretical one. At the same time, until 2018, the dynamics have
been multidirectional, indicating a potentially extremely low efficiency of influencing this indicator by
managing the region’s information environment. The use of this approach to management is expedient
only in combination with other, more effective tools. The coefficient of elasticity in this case is 0.42%,
which is logically justified.
Next, we consider the impact of changing the gap in the regional socio-economic system’s infor-
mation environment on indicator R3, “the number of crimes (rape) registered in the reporting period
under Art. 131 of the Criminal Code of the Russian Federation”. Based on the results of the analysis, the
following regression equation is obtained (formula 16):
R3i 30, 67 + 234, 46* Dipos
= (16)
The value obtained from Fisher’s F-test is 0.075, indicating the model’s sufficient level of sig-
nificance. The coefficient of determination is 0.43, which explains only 43% of the variance of the en-
dogenous variable, representing an insignificant result. A comparison of the dynamics of the actual and
theoretical values of
the endogenous variable is shown in Figure 8.
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 41
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
Figure 8. Dynamics of actual and theoretical values of
the number of crimes (rape) registered under
Art. 131 of the Criminal Code of the Russian Federation, depending on the gap in the level of positive
sentiment in the regional socio-economic system’s information environment (Karpenko, 2021)
As shown in Figure 8, the actual dynamics of the number of crimes (rape) registered in the re-
porting period under Art. 131 of the Criminal Code of the Russian Federation are comparable to the
theoretical one. However, the much smaller amplitude of the change indicates a relatively low level of
conversion of a potential managerial impact. The coefficient of elasticity in this case is 0.5%, which is
more significant relative to the indicators considered earlier. Thus, the management of the information
environment in the context of reducing the number of crimes (rape) registered in the reporting period
under Art. 131 of the Criminal Code of the Russian Federation is expedient only in combination with
other, more effective tools.
Next, we consider the impact of changing the gap in the level of positive tonality in the regional
socio-economic system’s information environment on indicator R4, “the number of crimes (hooligan-
ism) registered in the reporting period under Art. 213 of the Criminal Code of the Russian Federation”.
Based on the results of the analysis, the following regression equation is obtained (formula 17):
R3i 140,9 − 295, 269* Dipos
= (17)
The value obtained from Fisher’s F-test is 0.12, indicating the model’s insignificance. In combi-
nation with the inverse nature of the established relation, it can be unequivocally stated that the man-
agement of the information environment in the context of reducing the number of crimes (hooliganism)
registered in the reporting period under Art. 213 of the Criminal Code of the Russian Federation is
statistically inappropriate. An identical situation applies to indicator R5, “the number of deaths (suicide)
by main classes and individual causes of death per 100,000 people”. The value obtained from Fisher’s
F-test of the generated equation is 0.17, which also reveals the model’s insignificance.
Next, we consider the impact of changing the gap in the level of positive tonality in the regional
socio-economic system’s information environment on indicator R6, “the number of deaths (cases of
alcohol poisoning) by main classes and individual causes of death per 100,000 people”. Based on the
results of the analysis, the following regression equation is obtained (formula 18):
R6i 3, 016 + 20,12* Dipos
= (18)
The value obtained from Fisher’s F-test is 0.04, indicating the model’s high level of significance.
The coefficient of determination is 0.52, which is a relatively high result. A comparison of the dynamics
of the actual and theoretical values of
the endogenous variable is shown in Figure 9.
42 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
Figure 9. Dynamics of actual and theoretical values of the number of deaths (cases of alcohol poison-
ing) by main classes and individual causes of death per 100,000 people, depending on the gap in the
level of positive sentiment in the regional socio-economic system’s information environment (Karpen-
ko, 2021)
As depicted in Figure 9, the actual dynamics of the number of deaths (cases of alcohol poisoning)
by main classes and individual causes of death per 100,000 people are comparable to the theoretical one.
The minor structural breaks in 2016 and 2018 most likely have economic and social underlying causes.
The coefficient of elasticity in this case is 0.47%, which is significant enough. Thus, the management
of the information environment in the context of reducing the number of cases of alcohol poisoning is
quite appropriate.
In conclusion, let us consider a more specific indicator, which differs significantly from the previ-
ously considered “total number of unemployed in accordance with the methodology of the ILO” (R7).
The value obtained from Fisher’s F-test is 0.15, indicating the model’s insignificance. In combination
with the inverse nature of the established relation, it can be unequivocally stated that the management of
the information environment in the context of reducing the total number of unemployed is statistically
inappropriate.
5. Conclusion
In accordance with the confirmed conceptual model, it can be concluded that the volume of emis-
sions of harmful (polluting) substances into the air, the GRP per capita and real accrued wages as a per-
centage of those earned in the corresponding period in the previous year play a decisive role in managing
the region’s information environment. This specificity determines the primacy of economic factors in
the formation of a tonal gap in the information environment. Consequently, it is the economy that acts
as the primary mediator of the development of the regional socio-economic system. Thus, a direct ben-
eficial impact on the population’s welfare outside the context of improving the infrastructure and social
environment will significantly reduce the resulting indicators associated with mortality, whose con-
version can be effectively managed through continuous monitoring of the tonal gap in the information
environment and can affect the regional authorities’ provision of social security. However, regional spe-
cifics must also be considered. Since this model is specified for St Petersburg, based on its management
analysis, it is necessary to formulate a set of recommendations for the socially safe development of the
regional socio-economic system.
Acknowledgements
The research is financed as part of the project ‘Development of a methodology for instrumental
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 43
Study of the factors relevant to the management model for developing Russia’s regional socio-economic systems
base formation for analysis and modeling of the spatial socio-economic development of systems based
on internal reserves in the context of digitalization’ (FSEG-2023-0008).
References
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Karpenko, P.A., 2021. Mathematical Description of the Conceptual Model of Managing the Development of Regional Socio-Economic
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Labor and Human Development: University-Academic Collection of Scientific Papers, St Petersburg State University of Eco-
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Kulibanova, V.V., Teor, T.R., 2018. The Relevance of Identifying Groups of Stakeholders in the Context of the Regulation of Regional
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of Scientific Articles. Institute for Problems of Regional Economics of the Russian Academy of Sciences, St Petersburg State
University of Aerospace Instrumentation, St Petersburg, pp. 79–82.
Malakhova, L.A., Malakhov, V.P., Rakhimova, G.S., Korobkova, M.A., 2020. Management of Regional Social and Economic Systems, in:
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Nikonov, O.I., Krivorotov, V.V., Kalina, A.V., 2011. Methodological Approach to the Study of Sustainable and Safe Social and Economic
Development of the Territories.
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Regional Aspect. A Social Kaleidoscope 2(5), 102–112.
Rodionov, D.G., Karpenko, P.A., Konnikov E.A., 2021. The Method of Quantification of the State of Labor Resources in the Context of
Managing the Development of a Regional Socio-Economic System. Economic Sciences 197, 171–179.
Rodionov, D.G., Karpenko, P.A., Konnikov, E.A., 2021. Conceptual Model of Managing the Development of Regional Socio-Economic
Systems. Economic Sciences 197, 163–170.
Tatarkin, A.I., Doroshenko, S.V., 2011. Region as a Self-Developing Socio-Economic System: Crossing the Crisis. Economy of Regions
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3(10), 83–93.
Список источников
Basiago, A.D., 1998. Economic, Social, and Environmental Sustainability in Development Theory and Urban Planning Practice. Environ-
mentalist 19(2), 145–161.
Karpenko, P.A., 2021. Mathematical Description of the Conceptual Model of Managing the Development of Regional Socio-Economic
Systems of the Russian Federation. Bulletin of the Altai Academy of Economics and Law 9(1), 69–74.
Karpenko, P.A., Gazizulina, A.Y., Kikkas, K.N., Akri, E.P., Sharok, V.V., Papich L., 2018. Analysis of the Quality of Personnel Perfor-
mance Based on Social Characteristics, in: Proceedings of the International Conference on Soft Computing and Measurement:
FGAOU VO. St Petersburg State Electrotechnical University LETI named after VI Ulyanov (Lenina) 2, pp. 243–246.
Kharazishvili, Y., Kwilinski, A., Grishnova, O., Dzwigol, H., 2020. Social Safety of Society for Developing Countries to Meet Sustainable
Development Standards: Indicators, Level, Strategic Benchmarks (with calculations based on the case study of Ukraine). Sus-
tainability. 12(21), 8953.
Kisurkin, A.A., 2012. Factors Influencing the Innovative Development of the Region and Their Classification by Management Levels.
Modern Problems of Science and Education 2, 294.
Koshelev, E., 2023. Model of Motivation for the Top Management of Regional Government Agencies. Sustainable Development and En-
gineering Economics 4, 65–80.
Kulibanova, V.V., 2018. Investments in Human Capital as a Basis for the Innovative Development of the Region, in: Actual Problems of
Labor and Human Development: University-Academic Collection of Scientific Papers, St Petersburg State University of Eco-
nomics, St Petersburg, pp. 99–103.
Kulibanova, V.V., Teor, T.R., 2018. The Relevance of Identifying Groups of Stakeholders in the Context of the Regulation of Regional
Socio-Economic Systems, in: Problems of Transformation and Regulation of Regional Socio-Economic Systems: A Collection
of Scientific Articles. Institute for Problems of Regional Economics of the Russian Academy of Sciences, St Petersburg State
University of Aerospace Instrumentation, St Petersburg, pp. 79–82.
Malakhova, L.A., Malakhov, V.P., Rakhimova, G.S., Korobkova, M.A., 2020. Management of Regional Social and Economic Systems, in:
Proceedings of the First International Volga Region Conference on Economics, Humanities and Sports: FICEHS 2019. Atlantis
Press, 141–144.
44 Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2
Karpenko, P., Viktorova, N., Tran, H.H.
Nikonov, O.I., Krivorotov, V.V., Kalina, A.V., 2011. Methodological Approach to the Study of Sustainable and Safe Social and Economic
Development of the Territories.
Pastushenko, P.P., Obikhod, G.O., Khvesik, Y.M., 2021. Safe Guidelines for the Sustainable Socio-Ecological and Economic Development:
Regional Aspect. A Social Kaleidoscope 2(5), 102–112.
Rodionov, D.G., Karpenko, P.A., Konnikov E.A., 2021. The Method of Quantification of the State of Labor Resources in the Context of
Managing the Development of a Regional Socio-Economic System. Economic Sciences 197, 171–179.
Rodionov, D.G., Karpenko, P.A., Konnikov, E.A., 2021. Conceptual Model of Managing the Development of Regional Socio-Economic
Systems. Economic Sciences 197, 163–170.
Tatarkin, A.I., Doroshenko, S.V., 2011. Region as a Self-Developing Socio-Economic System: Crossing the Crisis. Economy of Regions
1, 15.
Voit, D.S., 2019. Management Models of the Region’s Economic Development in the Conditions of Socialization. Economic horizons
3(10), 83–93.
The article was submitted 11.01.2024, approved after reviewing 08.02.2024, accepted for publication 16.02.2024.
Статья поступила в редакцию 11.01.2024, одобрена после рецензирования 08.02.2024, принята к публикации
16.02.2024.
About authors:
1. Pavel Karpenko, researcher, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian
Federation. karpenko_pavel@mail.ru
2. Natalia Viktorova, Doctor of Economics, professor, Peter the Great St. Petersburg Polytechnic University, Saint
Petersburg, Russian Federation. https://orcid.org/0000-0002-7355-3541, viktorova_ng@spbstu.ru
3. Hoang Hieu Tran, Lecturer, University of Da Nang, Da Nang, Vietnam. https://orcid.org/0000-0001-5598-8245,
hieuth.due@gmail.com
Информация об авторах:
1. Павел Карпенко, соискатель, Санкт-Петербургский политехнический университет Петра Великого,
Санкт-Петербург, Российская Федерация. karpenko_pavel@mail.ru
2. Наталья Викторова, доктор экономических наук, профессор, Санкт-Петербургский
политехнический университет Петра Великого, Санкт-Петербург, Российская Федерация.
https://orcid.org/0000-0002-7355-3541, viktorova_ng@spbstu.ru
3. Хоанг Хиеу Чан, Лектор, Данангский университет, Дананг, Вьетнам
https://orcid.org/0000-0001-5598-8245, hieuth.due@gmail.com
Sustain. Dev. Eng. Econ. 2024, 1, 2. https://doi.org/10.48554/SDEE.2024.1.2 45
