=Paper=
{{Paper
|id=Vol-2830/paper17
|storemode=property
|title=Evaluation of Data and Simulation Modeling in the Implementation of the Smart City Concept for the Economies of Municipalities
|pdfUrl=https://ceur-ws.org/Vol-2830/paper17.pdf
|volume=Vol-2830
|authors=Olga Komarevtseva
}}
==Evaluation of Data and Simulation Modeling in the Implementation of the Smart City Concept for the Economies of Municipalities==
https://ceur-ws.org/Vol-2830/paper17.pdf
Evaluation of Data and Simulation Modeling in the
Implementation of the Smart City Concept for the
Economies of Municipalities
Olga O. Komarevtseva [0000-0002-4090-822X]
Plekhanov Russian University of Economics, 36 Stremyanny lane, Moscow, 115998, Russia
komare_91@mail.ru
Abstract. The relevance of the research topic lies in the lack of tools to assess
the level of the economy of the municipality from the perspective of the Smart
City concept. The purpose of the study is to use tools to implement the Smart
City concept in the economy of the municipality. The purpose is achieved by
changing the evaluation criteria and applying the simulation model. The results
of writing a scientific article are to consideration of the features of the Smart
City concept, to determination of indicators for assessing the Smart City con-
cept for the economy of the municipal formation, to the formation of a simula-
tion model of the economy of the municipal formation in accordance with the
Smart City concept. Research tools include the characterization method, the
theoretical representation method, the data grouping method, the estimation
method, the statistical method, the simulation method, the Bass diffusion meth-
od, the graphical method. Subsequently, the scientific article can be supple-
mented with an analysis of the Smart City concept for the economy of cities in
the Central Federal District.
Keywords: the municipal economy, the Smart City concept, the change man-
agement, the imitation, the risk, digitalization.
Introduction
Changing conditions and the process of economic management led to the estab-
lishment of new principles for the functioning of the municipality. The concept of the
Smart City has changed under the influence of the formation of the innovative direc-
tion of the territory, the technologicalization of the urban environment, the introduc-
tion of elements of the digital economy paradigm. The Smart City status is not as-
signed to all municipalities in the Smart City concept. Let's consider this statement in
accordance with the highlighted aspects.
Firstly, the high debt dependence and budget deficit of municipalities doesn’t allow
the active introduction of the Smart City concept [14]. This condition is associated
with building the innovative potential of the municipality. The Smart City concept
creates a technologically active urban environment. The Smart City concept is based
on the creation of an online platform [2]. The Smart City concept introduces infor-
mation and communication standards to improve the life of the population [9]. The
Smart City concept requires the development of a regulatory and legal framework
Proceedings of the 10th International Scientific and Practical Conference named after A. I. Kitov
"Information Technologies and Mathematical Methods in Economics and Management
(IT&MM-2020)", October 15-16, 2020, Moscow, Russia
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
[23]. For the municipality, statistical studies are carried out according to the given
estimated parameters of Smart-elements [6]. These postulates can be realized through
the possibilities of municipal budgets [15].
Secondly, “the overload” of the indicators of the statistical base doesn’t allow as-
sessing the level of the economy of the municipality on the basis of the Smart City
concept for [5]. This problem is related to two factors. On the one hand, the Smart
City concept indicators are assessed on the basis of eight criteria. Smart City criteria
include 15 or more statistical indicators [19]. On the other hand, statistical infor-
mation is lacking in some areas of the Smart City concept. This factor doesn’t allow
to form the final result of the development of the municipality [11]. For example,
official statistics don’t provide data on the indicators “the level of citizens’ involve-
ment in city management” [3]. Statistical studies include the indicator "“the level of
activity of Internet users” [21], the indicator “the level of civil initiatives on local
issues” [10]. The existing methodologies for assessing the Smart City concept are
conditional.
Thirdly, the models for the implementation of the Smart City concept aren’t
adapted to the Russian conditions for the development of the economy of municipali-
ties [13]. This drawback is based on the lack of elaboration of the regulatory and legal
framework and the Smart City design tool for the economy of municipal entities of
the Russian Federation. The problem that has arisen is based on the introduction of
digital technologies into the economy of the municipal formation [8]. The Smart City
concept isn’t strategic for the development of the economy of municipalities. The
Smart City concept is an element of the urban environment [18].
The selected aspects formulated the relevance of the research topic. To adapt the
Smart City concept to the economic conditions of the municipality it’s necessary to
simplify the existing paradigm. On the one hand, the methodology for assessing the
Smart City concept is formed for the economy of the municipality. On the other hand,
the directions of economic development of the municipality have been adjusted
through the Smart City concept.
The purpose of the study is to use tools to implement the Smart City concept in the
economy of the municipality. The purpose is achieved by changing the eval-uation
criteria and applying the simulation model. The objectives of the scientific article
include:
– to consideration of the features of the Smart City concept;
– to determination of indicators for assessing the Smart City concept for the
economy of the municipal formation;
– to the formation of a simulation model of the economy of the municipal for-
mation in accordance with the Smart City concept.
Literature Review
The Smart City concept for the economy of the territory is considered a tool, a
means of modernization and a change management system. The scientific worldview
within the Smart City tool focuses on the perception of the concept from the perspec-
tive of urban planning [32]. The basis of Smart City is the use of innovative means for
the development of the urban environment [24]. The Smart City concept as an eco-
nomic tool presupposes: the intellectualization of public safety [35], the introduction
of information city management [26], the formation of smart urban transport [30].
Another scientific position of the study of the Smart City concept is a means of mod-
ernizing the economy [34]. The Smart City concept implements technological mod-
ernization of the economy [22]. This modernization is based on improving the quality
of life of the population through the introduction of new generation technologies [28].
However, this scientific view does not take into account the problem of the high cost
of introducing technologies into the economy of municipal education [33]. The high-
lighted problem is associated with the limited budgetary funds of municipalities. On
the other hand, the Smart City concept is considered as a system for managing chang-
es in the economy of a municipal entity [27]. Change management is the process of
tracking risks and emerging conditions of uncertainty in the economy of a municipal
entity [31]. In our opinion, the Smart City concept is a change. This statement is due
to the fact that the Smart City concept transforms the economy of the territory [25]
and creates new relationships between agents of the local environment [29].
The Smart City concept is a system of conditions to ensure the modern quality of
life of the city population through the introduction of innovative technologies [1]. The
Smart City concept is based on innovative technologies. Innovative technologies are
synonymous with smart technologies. Smart stands as the key criteria for the concept.
The Smart City concept assumes the presence of directions of the urban environment.
Areas of the urban environment include the smart management [12], the smart tech-
nology [17], the smart environment, the smart ecology, the smart infrastructure, the
smart finance, the smart economy [7]. Features of the Smart City concept include the
formation of an efficient urban infrastructure based on the introduction of artificial
intelligence [4]. The Smart City concept introduces electronic processes for the partic-
ipation of the population of the municipality in matters of economic development of
the territory. Technologies are being introduced into the economy of the municipality
[16]. On the basis of the Smart City concept, an assessment of the conditions for the
development of the economy of the municipality is formed.
Methodology
The research apparatus is based on the implementation of the tasks set in a scien-
tific article. To highlight the features of the Smart City concept are the method of
characteristics, the method of theoretical representation. The formulation of indicators
for assessing the Smart City concept for the economy of the municipality includes the
method of grouping, the method of assessment, the statistical method. The formation
of a simulation model of the functioning of the economy of a municipal entity within
the framework of the Smart City concept are based on the method of simulation mod-
eling, the method of diffusion according to Bass [20], and the graphical method.
Result
In the concept of Smart City is a problem of a large array of data for conducting a
study of the economy of a municipality. Table 1 highlights the indicators of the Smart
City concept for assessing the economy of the municipality.
Table 1. Evaluation indicators of the Smart City concept for the economy of the municipality.
The direction The smart City concept assessment Evaluation indicators of
indicators the Smart City concept
The level of development of scien- The criterion for innova-
The smart economy tific and innovative activities, the
level of development of the Internet tive diversity ( I SC )
booking system, the level of devel-
opment of communication technolo-
gies.
The level of informatization of the The criterion of infor-
The smart management city and the openness of the city mation interaction of man-
government, the level of develop-
agement agents ( U SC )
ment of document circulation and
strategic planning.
The level of accessibility of the labor The criterion of intellectu-
The smart population market, the level of activity of Inter- alization of the population
net users, the level of use of elec- ( N SC )
tronic cards of students.
The level of development of uninter- The criterion digital sup-
The smart technology rupted access networks, the level of port area ( TSC )
development of telemetry, the level
of development of free wireless
access in transport.
The level of elimination of landfills, The criterion of ecological
The smart environment the level of monitoring of environ-
mental safety. safety ( E SC )
The level of development of car The criteria for online
The smart infrastruc- sharing, the level of development of
media ( FSC )
ture public transport, the level of availa-
bility of a network of filling stations
for electric vehicles, the level of
development of information systems
in urban planning.
The level of transparency of pro- The criterion of financial
The smart finance curement activities, the level of security ( S SC )
investment in the city's economy
In the context of assessment indicators of the Smart City concept, shortcomings are
formulated. The shortcomings of the Smart City concept don’t allow a full-fledged
study of the level of economic development of the municipality in accordance with
the highlighted postulates. Firstly, there is no calculation of the final result and it’s
impossible to draw a conclusion about the development of the economy of the munic-
ipal education. Secondly, the directions include many indicators for assessing the
development of the economy of the municipality. Thirdly, statistical information on
the indicators of the Smart City concept isn’t freely available. The system of indica-
tors of the Smart City concept isn’t adapted to the statistical reports of the statistical
services of the Russian Federation. The highlighted circumstances formulated the
importance of forming the Smart City concept. The indicators for assessing the Smart
City concept for the economy of the municipality are presented in Table 1.
Indicators for evaluating the Smart City concept for a municipal education econo-
my include:
1. The criterion for innovative diversity ( I SC ):
P p n G
I SC
Ce Ci
In
, (1)
where I SC is the criterion for innovative diversity, P is the volume of shipped inno-
vative products, goods and services (million rubles), pn is the scientific and innova-
tive potential of the municipality, Ce is costs of re-equipping the economy towards
technological equipment (million rubles), Ci is costs of introducing information sys-
tems into the economy of the municipality (million rubles), G is the amount of grants
received by scientific and educational organizations of the municipality in the current
year (million rubles), I n is the total cost of intellectual property products registered
on the territory of the municipality (million rubles).
2. The criterion of information interaction of management agents ( U SC ):
U SC
I k u Iu u , (2)
I k 1 i Iu 1 o
where U SC is the criterion of information interaction of management agents, I k is the
number of citizens' initiatives registered within the framework of appeals to local
governments in the current year (conventional unit), I k 1 is the number of citizens'
initiatives registered in the framework of appeals to local governments in the previous
year (conventional unit), ui is the level of development of information systems of the
administration of the municipality, I u is the number of satisfied applications of citi-
zens of the municipality, out of the number registered in the current year (convention-
al unit), I u 1 is the number of satisfied applications of citizens of the municipality,
from the number registered in the previous year (conventional unit), uo is the level of
information transparency of the authorities of the municipality.
3. The criterion of intellectualization of the population ( N SC ):
N SC
Ki u K n u , (3)
Kb d K a a
where N SC is the criterion of intellectualization of the population, K i is the number of
jobs in the innovation sector of the economy of the municipality (conventional
unit), K b is the number of unemployed in the municipality (people), u d is the level of
accessibility of labor market information, K n is the number of people working in the
scientific and educational field (people), K a is the number of economically active
population of the municipality (people), u a is the level of activity of Internet users of
the municipality.
4. The criterion digital support area ( TSC ):
TSC Z u Z g ,
ki ie (4)
where TSC is the criterion digital support area, Z u is the level of use of digital tech-
nologies in the daily life of the population of the municipality, Z g is the level of digi-
tal literacy of the population of the municipality, ki is the coefficient of infrastructural
accessibility of digital technologies in the territory of the municipality, ie is the indi-
cator of the effectiveness of using digital technologies for the economy of the munici-
pality.
5. The criterion of ecological safety ( ESC ):
E SC pe k p pn k v , (5)
where ESC is the criterion of ecological safety, pe is the indicator of increasing the
rate of environmental pollution of the territory, k p is the coefficient of economic
peril, pn is the indicator of excess of standards for the level of waste, kv is coefficient
of harmful environmental impact, rendered by the enterprises of the municipality.
6. The criteria for online media ( FSC ):
FSC S o S n , (6)
where FSC is the criteria for online media, S o is the amount of transactions made
online (within the framework of infrastructure and transport services) (million rubles),
S n is the amount of cash transactions (within the framework of infrastructure and
transport services) (million rubles).
7. The criterion of financial security ( S SC ):
D F Z ur
S SC
RM K
B
, (7)
where S SC is the criterion of financial security, D is the indicator of budget revenues
of the municipality (million rubles), F is the indicator of financial result from the
activities of enterprises located on the territory of the municipality (million rubles), R
is the indicator of budget expenditures of the municipal formation (million rubles), M
is the indicator municipal debt (million rubles), K is the indicator of accounts payable
of enterprises located on the territory of the municipality (million rubles), Z is the
amount of funds saved in the framework of procurement activities (million rubles), B
is the amount of non-cash transfers within the framework of social and economic
services for the population (million rubles), u r is level of development of the banking
system of the territory.
The indicators reflect the specific direction of the Smart City concept for the econ-
omy of the municipality. The direction of smart economy is the criterion for innova-
tive diversity, the direction of smart management is the criterion of information inter-
action of management agents, the direction of smart population is the criterion of
intellectualization of the population, the direction of smart technology is the criterion
digital support area, the direction of smart environment is the criterion of ecological
safety, the direction of smart infrastructure is the criteria for online media, the direc-
tion of smart finance is the criterion of financial security. The evaluation of the crite-
ria is based on a positive result or a negative result. A positive result indicates the
formation of a direction in the economy of the municipality in the context of the
Smart City concept. The negative result indicates that the Smart City concept is not
typical for the economy.
The final results of the criteria for the Smart City concept are presented on the ex-
ample of the economy of the municipal entity of the city of Orel (Table 2).
Table 2. Evaluation indicators of the Smart City concept for the economy of the
municipal education of the city of Orel
Год I U SC N SC
SC TSC E SC FS C S SC
2017 -1,6 -1,42 -1,86 -0,18 -2,42 1,32 -0,9
2018 -0,84 -1,25 -1,58 -0,82 –3,24 3,42 –0,88
2019 – 0,15 –1,20 –1,42 –0,90 –4,01 4,15 –0,82
The direction of smart economy for the economy of Orel is typical in the period
2017–2019 years. The economy of Orel partially contained elements of the Smart
City concept in 2017–2019 years. Forecasting the development of the economy of
Orel wasn’t carried out within the framework of the Smart City concept for the entire
study period. We will form a simulation model of the functioning of the municipal
economy within the framework of the Smart City concept and the existing changes.
The AnyLogic software is the tool for simulation modeling. The method of imitation
is the Bass diffusion. The basis of the simulation model is to obtain the Smart City
model for studying the economy of the municipality of Orel in a long-term period.
The simulation model should show whether the economy of Orel will develop within
the Smart City concept in 2025 year.
The initial stage of the simulation model is to check the final result of the direc-
tions of the Smart City concept. The simulation model of the
Smart City concept based on the example of the city of Orel is formulated on the
basis of storage devices. The drives reflect the main directions of the Smart City con-
cept. The directions are identical to the drives. So, the Orel drive is the municipality
of Orel. The Economy drive is direction of smart economy. The Management drive is
the direction of smart management. The Population drive is the direction of smart
population. The Technology drive is the direction of smart technology. The Ecology
drive is the direction of smart environment. The Information drive is the direction of
smart infrastructure. The Finance drive is the direction of smart finance. The direction
criteria of the Smart City concept are represented by dynamic variables. Dynamic
variables implement a predictive function due to the given parameters and cyclical
tuning of the economy of the municipality. The designation of dynamic variables is
based on a criterion value. For example, the criterion for innovative diversity identical
I SC . The simulation model parameters are value-based. The model values reflect the
final result of the dynamic variables. For example, for the criterion of innovative di-
versity, the set of variables include P is the volume of shipped innovative products,
goods and services, pn is the scientific and innovative potential of the municipality, Ce
is costs of re-equipping the economy towards technological equipment, Ci is costs of
introducing information systems into the economy of the municipality, G is the
amount of grants received by scientific and educational organizations of the munici-
pality in the current year, I n is the total cost of intellectual property products regis-
tered on the territory of the municipality.
The next stage in the formation of the simulation model is the simulation assess-
ment of indicators of the Smart City concept for the economy of Orel. For example,
let's create the Economy drive with a given dynamic variable and parameters for 2019
year. The final result of the development indicator for the smart economy direction
for the economy of Orel is 0.15 in 2019 year. This condition must also be met within
the simulation model. The Economy drive with parameters and variable values of
2019 year (Fig. 1).
Fig. 1. Simulation of the smart economy direction of the Smart City concept on the
example of the city of Orel
The resulting model in the direction of smart economy reflects the negative value
of the criterion of innovative diversity. The value of the criterion of innovative diver-
sity for the direction of smart economics of municipal education in Orel is -0.15. The
formulated condition allows us to conclude about the accuracy of the generated simu-
lation model of the smart economy direction for the city of Orel.
The purpose of using simulation modeling is the formation of the Smart City mod-
el for studying the economy of the municipality of Orel with a predictive function
until 2025 year. This condition is necessary to determine the primary directions of the
economy of the municipal education of the city of Orel. The priority areas will allow
the Smart City concept to be implemented in the economy of the Orel municipality.
To simulate the model, we will form the estimated accumulators with the given dy-
namic variables and parameters of the economy of the municipal formation of the city
of Orel. The forecasting lag is up to 2025 year. The limitations of the simulation mod-
el include the risk components from changes in the external environment and the
transformation processes of legislative acts in the field of the digital economy. These
restrictions are determined by the level of cyclicity of dynamic variables. The final
model of the Smart City model for the study of the economy of the municipality of
Orel is presented in Fig. 2.
Fig. 2. The Smart City model for studying the economy of the municipality of Orel
The Smart City model for researching the economy of the municipality of Orel
made it possible to establish a positive result of the smart economy direction and the
smart infrastructure direction by 2025 year. Due to the development of these areas,
the economy of the municipality of Orel can function on the basis of the Smart City
model. An important feature of the model is the allocation of negative results in the
directions of the economy of the municipal city of Orel. The negative dynamics of the
drive indicates the problems in the functioning of this direction in the economy of the
city of Orel. Negative dynamics is produced in the context of changes in indicators for
2019 year compared to the forecasted values of 2025 year. The directions of the econ-
omy of Orel with negative dynamics are the Technology drive and the Ecology drive.
These directions require the formation of software products for the development of
the territory of the city of Orel.
Discussion
Scientific research made it possible to identify several problems. Firstly, some
economies of municipalities aren’t adapted to the development conditions of the
Smart City concept. Secondly, there is no connection between the statistical indicators
of the Smart City concept and the socio-economic reports of municipalities. Thirdly,
simulation modeling isn’t considered as a tool for forecasting the processes of intro-
ducing the Smart City concept into the economy of a municipal entity in the long
term. These problems require discussion in further scientific research. Subsequently,
the scientific article can be supplemented with an analysis of the Smart City concept
for the economy of cities in the Central Federal District.
Conclusion
The conducted scientific research has led to the following conclusions.
1. The Smart City concept hasn’t been tested for the current state of most munici-
pal economies. The main disadvantages are to the lack of final results for evaluating
the Smart City concept, to the overload of methods with the number of indicators
when studying the states of the territories within the Smart City concept, to the impos-
sibility of obtaining statistical data within the Smart City concept.
2. Based on the presented shortcomings, we form Smart City the concept for study-
ing the economy of a municipal entity. This concept includes nine areas for assessing
the economics of municipal education. These areas are assessed on the basis of crite-
ria for the implementation of the Smart City concept: the criterion for innovative di-
versity, the criterion of information iteraction of management agents, the criterion of
intellectualization of the population, the criterion digital support area, the criterion of
ecological safety, the criteria for online media, the criterion of financial security.
3. Forecasting is manifested through the simulation of the Smart City concept for
the economy of the municipality. For example, the values of indicators of the econo-
my of the municipal formation of the city of Orel. The forecasting lag is 2025 year.
As part of the study, it was established that the main directions of development of the
city of Orel are the smart economy direction and the smart infrastructure direction by
2025 year. The attention of the executive authorities of the city of Orel requires the
areas of the smart environment direction and the smart technologies direction. These
directions show negative dynamics throughout the study period.
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