ENTERPRISE DEVELOPMENT MANAGEMENT THROUGH MANAGED CHAOS
Nataliia Kasianova
National Aviation University, Ukraine
E-mail: kasianova_n@nau.edu.ua
Elena Tarasova
Altai State University, Russian Federation
E-mail: tarasovaea@sch2009.net
Nataliia Kravchuk
National Aviation University, Ukraine
E-mail: 0509133222@ukr.net
Submission: 11/09/2018
Revision: 11/23/2018
Accept: 12/09/2018
ABSTRACT
The purpose of the study is to substantiate the
feasibility of using the theory of chaos in the process of managing the
industrial enterprises. One of the tools for managing chaos is proposed to be
chaos engineering – a method of conducting planned experiments that give an
idea of how the system can behave as a result of disturbances. The introduction
of chaos engineering will allow for prediction of possible perturbations and
prepare the system for a new attractor at an optimal time with minimal losses. The
chaos management model of the economic system, which allows either a radical
change in the status of the enterprise, its ability to influence demand and
supply while maintaining the subjectivity of the development, or to promote antifragility
of the enterprise, allows strengthening the stability of the economic system.
Keywords: microeconomic
system, antifragility, chaos management model
1. INTRODUCTION
The current situation in the world is
characterized by the expansion of the global systemic crisis, increased competition,
the growth of uncertainty, risks and instability in all spheres and at all
levels of the economy. Among the new, dynamic scientific disciplines of the
twenty-first century, the concept of "controlled chaos", the theory
of "entropy logic" and "entropy economy" occupy a leading
place. A new interdisciplinary field of research is actively developing, which
can be generally called the "science of chaos", whose subject matter
is systems with nonlinear dynamics, unstable behavior, self-organization effects,
the presence of chaotic regimes and bifurcation.
In the
modern world, it is particularly important to study the possibility of
controlling the generation of chaos, the behavior of complex nonlinear systems
and the manifestation of instability, as well as the possibility of a partial
determination of the behavior of the system in a turbulent world. The theory of
controlled chaos began to develop in the 80 years of the last century. In this
theory, the means of creating a controlled chaos of systems are determined. In
the application of this theory, the system is artificially transformed into a
state of chaos. Managed chaos – the main element of the construction of chaos
point of the new attractor, the transition to a new state of order.
According to Mann (1992), “Chaos
can change the method by which we view the entire spectrum of human
interactions ... We can learn a lot if we consider chaos and regrouping as
opportunities, and not rush to stability”. A definite contribution to the
development of the theory of critical complexity (chaos) was made by Waldrop (1992),
who published the work “Complexity: A New Science at the Turn of Order and
Chaos”.
According to Kiel and Elliott (1996),
“the theory of chaos today represents the main area of the exact sciences, the
achievements of which representatives of the social sciences integrate into
their theory and methodology”. However, in their opinion, it is more
significant that chaos theory is perceived as a means to explain and identify
many aspects of uncertainty, nonlinearity, unpredictability in the behavior of
socio-economic systems. We can also mention the work of the French scientist Ramonet (1998) “The geopolitics of chaos”, in which the
concepts of the geopolitical theory of chaos are developed.
PhD and financial investor Williams
(2004) applies chaos theory when developing strategies and algorithms for
financial transactions. the activity of raiders and investors. His work
“Trading Chaos” is best known. According to B. Williams, in accordance with the
theory of chaos, an investor who starts from a linear perspective will never
see the real market, thereby risking sustained losses. For the success of the
financial market, you need to use the tools of chaos theory - nonlinear,
fractal analysis.
It is also necessary to cite the
work of the American researcher Peters (1994) "Fractal
analysis of financial markets. The application of chaos theory in investments
and the economy”, which are devoted to the analysis of the modern problem of
nonlinear economic dynamics (economic synergetics),
proposes long-term forecast methods for stock markets, bonds, currencies, as
well as fractal analysis of stock markets , bonds and currencies.
The problems of managing complex
systems in terms of entropy engaged in such scholars as Hacken
(1985), Prigogine and Stengers (1986), Lepsky (2009), Malinetsky (1998),
Akhromeeva and Kurdyumov (2007).
These scientists have developed the
foundations of the theory of chaos. But the question of using the elements of
dynamic chaos to the management of microeconomic systems in modern science has
practically not been considered.
The
traditional approach considers chaos solely as a negative category, that is,
the main purpose of any directed intervention in natural, social or economic
processes is to minimize chaos. However, synergetics
reveals the positive role of chaos. In reality, all processes occur unevenly:
quiet periods are replaced by tense critical states, when it is necessary to
decide on the further development of the system.
At such
moments the decisive role is played not by order, but by chaos. Without this
disordered, uncontrolled, random component, no qualitative changes are
possible, the system transition to a qualitatively new state. The theory of
chaos says that complex systems are extremely dependent on the initial
conditions and small changes in the environment lead to unpredictable
consequences.
Chaos
gives more opportunities to jump to increase the potential of the system, and
most importantly – to sharply change the trajectory and the very logic of its
development. The chaos initially provides the possibility of an ascent of the
system with the former trajectory in case of loss of stability in the zone of
crisis, and then helps to connect to the new attractor, causing obstacles along
the way. It is in this that the constructive role of chaos manifests itself.
The synergetic economy shows that chaos lies in the nature of any economic
system.
Most
scientists consider the problems of managing chaotic systems at the level of macroeconomic
systems. At the same time, similar chaotic processes are characteristic of
microeconomic systems. Thus, an industrial enterprise can be considered as an
open microeconomic system, the behavior of which is described by trajectories
in a certain space.
Changing
the trajectory is a change in the system evolution program. In this sense, the
transition from stability to chaos can give a new impetus to the development of
the system, contributes to the transition to a fundamentally new level of organization
and management. In the case of a successful overcoming of chaos, the efficiency
of microeconomic management is significantly enhanced.
Based
on the above, under the control of the chaos of the microeconomic system, we
will understand the process of changing the evolutionary vector of development
into a revolutionary to achieve the global goal of the existence of the system.
When managing the development of a company as a microeconomic system, two
complex tasks can be solved, namely: elimination of imbalances, deviations from
planned system behavior and creation of contradictions as the source for its
further development.
2. THEORY
One of
the possible tools for controlling chaos, in our opinion, is chaos engineering
(shaos engineering) – it is actually "injection"
of external and internal influences, the ability to check the system's ability
to react to disturbance. This is an effective method for practicing, preparing
and preventing / minimizing losses before they occur in reality. Incorrectly
consider chaos engineering as a chaotic process. In fact, chaos technology
includes planned experiments that show how the system can behave as a result of
disturbances. These are experiments in which a hypothesis about the behavior of
the system is formed, impacts that improve the system are evaluated. The time
and power of the control effects are determined to prevent negative pressure on
the system.
An
important principle of technology of chaos engineering is minimization of the
radius of an explosion – negative changes, which increases the confidence in
the system and understanding the extent of potential risk.
The
concept of chaos engineering is based on the category of
"antifragility" introduced by Taleb (2014).
Antifragility is the ability to benefit from failures, losses, errors; the
ability to harden, develop and become stronger when faced with chaos (TALEB,
2014). The concept of antifragility is
widely used in living organisms (ecology, physiology, psychology, etc.) and
relates to the ability of the system to actively overcome problems and adapt to
the new situation.
Antifragiliting systems are amplified under
the influence of stress factors, and the gain is due to prediction and hypercompensation:
·
the system receives signals
about the change of the environment;
·
the system predicts that now
this will always be, and is rebuilt with a stock;
·
being prepared for a certain
level of stress, the system is ready to move to a higher level.
There are
two important points in this picture. First, we are talking about acute
stressors (acute stressors). Chronic, monotonous stresses lead to fatigue and
deterioration of the system, not to its development. Second, the system must
respond with hyper compensation, and not an equal response to the stressor. In
this case, the system will be antifragility in relation to these influences.
Taleb
claims: accidental shocks are beneficial for the enterprise to a certain
extent. This limit is determined by how much the company has excessive stocks.
The form of redundancy for a company is the availability of potential reserves.
The presence of excessive resources allows for the implementation of antifragility and invulnerability.
True, those who are regularly engaged in material provisioning or regularly
insure all their risks, not so much. In addition, the material stock in itself
is not antifragility.
Antifragility goes
beyond the limits of stability, because it implies the evolution of a system
capable of developing as a result of the stress it was subjected to to adapt to new possible "failures." Stability is
defined as the ability to "absorb" destabilizing factors that can be
caused by stress factors. Antifragilition company is not afraid of changes in the
external environment and more often comes out of them with additional profits
than with losses.
In economics, the state of anti-frailness means that,
following a certain decline, loads, a rapid upward movement begins that
compensates for losses. It is necessary for the company to constantly endure
certain stresses, failures, overcome difficulties. Awakening the system using
random noise to improve its performance is used in many areas. Chaotic systems
can be stabilized by adding randomness. Chaos turns into order, not because
there is less chaos in the system, but because random, absolutely random
fluctuations of low intensity have been added to it. This implies an important
practical principle: in order to increase the stability of the system, it is
sometimes necessary to add random perturbations to it.
Thus, the implementation of chaos-based controlled
chaos strategy implies a certain "chaosification"
of the system in a controlled manner, which will allow for prediction of
possible disturbances and prepare the system for the transition to a new
development trajectory at the optimal time with minimal losses. Thanks to chaos
engineering, you can achieve a deeper vision of the effects of chaos in order
to improve the stability of the system. This, ultimately, is the basis for
creating more mature and reliable systems that can recover and reduce harm in
the event of a serious security incident.
Thus, the purpose of the study is to construct an
economic and mathematical model of chaos management of a microeconomic system
that allows one to determine: crisis points of system operation, the impact on which
can lead the system to chaos; controlling influence of chaos management, which are
formed in accordance with the chosen attractor.
3. RESEARCH METHODOLOGY.
Linear and narrow-disciplinary approaches within the
limits of modern classical economic theory are not able to explain and predict
contemporary problem parts of socio-economic development caused by nonlinear
laws of entropy economy and chaos. In this regard, it is relevant and promising
to consider the regularities of the transformation of the functioning of
economic systems on the basis of the synergetic paradigm.
The
model of chaos management, like any other model, in a constructive way can be
fully described using four system elements: function, input, output, processor. When
constructing a model for managing the chaos of a particular microeconomic
system, it is important to fix the zones of intersection of the interests of
the existing actors of the economy –
"power centers" (shareholders and managers of the company). At the
same time, such an effect may be destabilizing, requiring fixation in the model
of contradictions (crisis) points by type, group and level, and possible
options for their solution.
Schematically, a model for controlling the chaos of a
microeconomic system can be represented as follows (Figure 1).
The
function performs a system-forming role and characterizes the purpose of the
model. The function defines what should be achieved as a result of the
operation of the chaos management model, but does not indicate how this should
be done. The objective function of the model involves the formation of control
effects aimed at the purposeful transformation of the status or complete change
of the microeconomic system as the main object of influence of the model. The
system components of the company are subject to influence, determining its role
and place on the market, the ability to sustainable development: administrative
bodies, socio-economic and financial potential, infrastructure, territory and
labor resources. The task is to radically change the status of an enterprise,
which is determined by its position in the global and regional system, its
ability to influence demand and supply while maintaining the inherent
subjectivity of its development, or to promote its antifragility, which implies the ability to protect and strengthen
its interests, to provide economic security.
Figure 1: Chaos management model of the microeconomic
system
The
model uses a set of tools to create the chaos of the microeconomic system, of
which the most common are measures to support existing areas of enterprise
development. Along with this, a deliberate introduction of the idea that
advancement in this direction will inevitably lead to a decline in the
competitiveness of the enterprise, technological lag and loss of positions in
the market. The target function of the model reveals the designation of the
model and involves the development of managerial actions aimed at increasing the
level of conflict in the economic sphere, destabilization of production,
distribution, exchange and consumption. The target function determines what
should be achieved as a function of the system, but does not indicate how this
should be done.
The
managerial influences on the input of the chaos management model are formed in
accordance with the chosen scenario of the development of the situation within
the enterprise and in its environment, as well as situations that arise in the
scenario. The input of the model is influenced by various factors – challenges,
risks, dangers and threats that are generated in the scenario of controlled
chaos and situations that arise when the model operates in accordance with this
scenario.
At
the exit between the different levels of management of the model implemented
tasks of information exchange, control, management and feedback. At the output
of the model, solutions are generated that are transmitted to different
performance levels acting in the interests of the model within the
microeconomic system and beyond.
The
processor as an important system characteristic of the model provides a
comparison of the current state of economic spheres with a given level. The
monitoring system creates a feedback channel that ensures the stability of the
model to chaos engineering and allows for continuous operational control and
assessment of the impact of the decisions made on the situation within the
microeconomic system.
A
description of the model of chaos management can be presented as a matrix of
system components that can be described by characteristics within the four main
dimensions of the model: static, control, dynamic and predictive.
Among
the main system components of the model of management of chaos include:
a) Functions
and goals of the model. It should be noted that for the implementation of
various purposes, transformation of the model may be required, up to the
necessity of creating a new model.
b) The
purpose of the model, which is based on the presentation of the interested party
in the final results of the functioning of the model, and that the model can
really provide for their achievement. The designation of the model is a leading
criterion in determining its structure, overall potential and other
characteristics, taking into account the expected contribution of the model to
the achievement of the final result.
c) The
area of responsibility of the model allows to determine the extent to which
activities are carried out to form the totality of necessary transformations in
order to create a situation of controlled chaos (global or local).
d) Processor
model is the most important system characteristic. In general, the processor
may include:
·
an algorithm that defines the sequence of development
and implementation of decisions that ensure the achievement of the goals and
objectives of the model;
·
basic resources of the model, including material,
technical, financial, information, infrastructure for ensuring the activity of
the model in its area of responsibility;
·
a catalyst, which includes a set of internal factors
that ensure the processes of transforming the actions of external factors into
managerial influence (competencies of the model and their correspondence to the
goals and objectives, the efficiency of the development and decision making
procedures, the ability to design financial and industrial influence within the
area of responsibility of the model);
·
labor resources, which are involved in solving
problems of the model at the stages of its implementation.
e) Strategic
stability of the model in different situations. Among the factors that provide
strategic stability, one can attribute the presence of a clear strategy; the
internal unity of the participants interested in achieving the ultimate goal of
the model; the ability of the organizers to ensure the formal compliance of the
measures taken with the recognized legal and regulatory framework.
f) Network
of model links with other participants in the economic process, interested in
transforming the microeconomic system. The network may include individual
enterprises, their associations, external organizations, individual influential
personalities.
g) Monitoring
implies the presence in the model of the developed network of means of
observing the situation, systematization and analysis of information and their
operational transmission to decision-making centers. The presence of a
monitoring system ensures the functioning of the feedback channel, which is a
key condition for the stable operation of the model as a whole.
In
the architecture of the chaos management model, an important place belongs to
the processor, which has a number of significant differences, for example, from
the processor model to ensure the economic safety of the system. If the
processor of the security model can clearly define hierarchical levels of
management: strategic, operational and tactical, then the chaos processor model
will look different.
The
system difference consists in combining the possibilities of hierarchical
management structures in it and have already declared themselves phenomena of
network structures capable of serving as a powerful tool that has a
destabilizing effect on all areas of the microeconomic system. Within the
framework of synergistic interaction, these system components complement each
other's advantages and mutually compensate for the disadvantages, which ensures
the flexibility of their application at various stages of the chaotic operation
of the system.
Thus,
traditionally rigid hierarchical control system has inherent subordination,
stability, restoration, availability of channels of information transmission.
However, the hierarchical structure often has a low degree of manageability and
a systemic tendency to increase the number of hierarchical stages, lack of efficiency
in the transmission of information, which leads to delays in decision making
and action in real time. Hierarchical structures often die when the central
link is destroyed. It is such a hierarchical structure in the form of
organizational structure of the enterprise and opposes the model of management
of chaos.
Taking
into account the specifics of the processor of the model of chaos management,
another important feature is the possibility of its timely functional
rearrangement. This ensures the mobility and mobility of the use of basic
resources, for example, their focus on a strategically important goal.
In
general, the presence of high-speed connections and the potential of flexible
adaptation facilitates better coordination with sharp and difficult predicted
changes in the situation. Variability and manageability of the boundaries of
the model allow modifying the composition of the network as a response to such
changes. The use of network forms of organization and interaction allows for
the survival and effectiveness of chaos management models.
The
algorithm for implementing the chaos management model directly with the
functions of management and development of solutions and provides the
implementation of the scenario through the implementation of a clearly defined
sequence of actions.
The
task of managing chaos is to obtain the corresponding laws of governance. The
laws must maintain the desired levels of stability and chaos, stable
development and change of entropy should proceed according to equations that
reflect the natural nature of the system's behavior.
If
the result of the implementation of the model of chaos engineering should be
the transition from one attractor to another with the preservation of the
enterprise as an object of management, then the control parameters can only be
used to change the current state and, at the final stage of control, connect to
the entropy management. The growth of entropy should tend to some limited
extent that the microeconomic system is able to control. Such chaos management
can only be used in interphase transitions of the system's development. These
transitions are very short-lived and sensitive to external influences. When
using chaos-engineering in other periods, the system, after getting off the
trajectory of development, returns to the old attractor again after a certain
period of time, increasing its antifragility.
In such periods, the transfer to a new attractor will require enormous costs of
"managing" chaos resources.
4. RESULTS AND DISCUSSION
The
above can make an important conclusion: when managing chaos based on the
confrontation between entropy s and
the current state x, it is expedient
to select such optimal attractors , the
motion of which approximation was determined by the equations describing the
stabilization of processes on the asymptotic behavior. The choice of such a
manifold
determines the natural nature of the
interaction of entropy and the current state, and corresponds to a
self-similar, self-consistent behavior of the processes of self-organization of
the system.
A
powerful instrument for controlling nonlinear objects, the application of which
has been recently devoted to a significant number of publications, is the
method of analytical design of aggregate regulators (ADAR) (KOLESNIKOV, 2012).
Let
the microeconomic system be described in the state space by a system of
equations of the form:
(1)
where and
are some
functions that depend on the level of chaos s,
the current state x; u – a
controlling influence that can be defined as
(2)
ADAR method is a solution of the system of functional
equations of the form
(3)
allows
to synthesize a state regulator that provides the system not only asymptotic
stability but also the main direct indicators of the current state and entropy,
as well as the static accuracy provided by the choice of the form and
parameters of function (3), where ψ
are some aggregated changes in the control influence u, which provide the
transition of system (1) from a certain initial state to a small
neighborhood of the solutions of the equation
, the transition to the desired state of the system.
The controlling influence (2) allows maintaining the
trajectory of the system's development in the required neighborhood at its
motion along the given curve
.
In terms of synergy, a variable is a generalized order
parameter (the main variable when describing the operation of a system, for
example, a function that establishes the connection between the growth of
entropy and the current state), which reflects the properties of the system.
The introduced parameter of order is a kind of "informer", which acts
as the transmitter of information about the processes occurring in the economic
system. The parameter of order indicates the state of flow of purposeful
processes of self-organization in the system. Consideration of the variable as
a generalized order parameter, makes it possible to make such an
interpretation, optimizes the functional.
According to G. Hacken
(1985), the microscopic measure of action for any self-organizing system is the
square of the order parameter. The measure of microscopic action can be
conventionally called the work performed by the system for the creation of
entropy. For these reasons, it is expedient to introduce into
the accompanying functional J the
quadratic components 𝜓2,
which reflect the degree of microscopic action of the systems obtained. The
efficiency of the system in synergetics is the rate
of change from the performed measures, which means the introduction of the
derivative in the
accompanying functional J. The weight
coefficient T specifies the time of
development of the economic system from the moment of the start of management
to the entrance to the attractor zone.
Assume that the management of enterprise chaos changes
the type of equilibrium functions that can occur when changing the values of
system parameters. Parametric method of management correspond to methods of
creating chaos and the destruction of the current state of the enterprise. In
the initial formulation, the task of managing an enterprise is determined by
differential equations, to which are added external forces that consist of the
corresponding management influences u(t).
For the emergence of the phenomenon of self-organization, it is necessary that
the external forces included in the model prove to be internal. To do this, you
need to move from the original to the expanded task, taking into account that
external forces have become internal interactions of the general system.
Let k(s, x)
– the coefficient of stability of the enterprise development, depending on the
purpose of development and on the level of available potential, L(х) – capacity depreciation
coefficient, – function
describes the behavior of chaos.
Consider the following model:
(4)
Introduce the function that describes the possible
variety:
(5)
It is necessary that the function
ψ satisfy the characteristic
differential equation . From equation (5) we find
and obtain the
equation
(6)
which
puts the system , where the coefficients
and
are partial
derivatives of the corresponding coefficient.
The system of differential equations (4) is
transformed into a system under the influence of the received control influence
, (7)
which
describes the development of the entropy and the gravitation of the current
state of the enterprise to the attractor .
According to official statistics, more than a third of
Ukrainian enterprises currently have signs of instability (Table 1). You can
see a significant imbalance in the statistics.
Table 1: Financial results of Ukrainian enterprises
|
|
Indexes |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
|
Industry |
financial results, mln. UAH |
21353,4 |
13698,3 |
-166414,0 |
-181360,9 |
-7569,6 |
85429,5 |
|
margin,% |
3,4 |
3,0 |
1,6 |
0,9 |
4,2 |
6,6 |
|
|
% of companies that received damage |
37,6 |
36,7 |
36,7 |
27,1 |
27,2 |
28,4 |
|
|
Manufacturing |
financial results, mln. UAH |
-1842,4 |
5526,9 |
-135282,9 |
-121774,3 |
-25938,2 |
23592,3 |
|
margin,% |
1,8 |
2,1 |
-0,6 |
0,7 |
3,0 |
4,4 |
|
|
% of companies that received damage |
35,9 |
34,8 |
34,8 |
24,9 |
24,8 |
30,9 |
|
|
Engineering |
financial results, mln. UAH |
13322,8 |
5526,9 |
-20501,5 |
-12651,6 |
1696,2 |
9023,3 |
|
margin,% |
9,9 |
6,6 |
-2,4 |
3,4 |
8,0 |
9,3 |
|
|
% of companies that received damage |
33,0 |
34,8 |
35,3 |
25,9 |
22,8 |
22,6 |
Source: Financial
results of large and medium-sized enterprises before taxation by types of
economic activity
Thus,
the number of unprofitable enterprises in industry is gradually decreasing, but
losses from economic activity are increasing. This can be explained by the loss
of economic stability by individual enterprises, especially large-scale
businesses, whose loss-making has a significant impact on the industry as a
whole.
The
negative factor on the way of development of industrial enterprises of Ukraine
is the outdated potential – production funds of III-IV technological processes,
the maintenance of which is rather costly, and produced products –
uncompetitive. However, the experience of the functioning of industrial
enterprises, which occupy the leading position in the industry, shows that the
imbalance of economic processes that exists both at the macro and micro levels,
can entail not only threats, but also be a stimulus to start a new cycle system
development.
The
simplest program of elementary catastrophe forecasting, which is an indicator
of the chaotic state of the economic system, can be built on the basis of data
on the relationship of variables that characterize its behavior. If it is
established that between the variables characterizing the behavior of the
system, the relation is described by the polynomial of the third degree of the
species
, (8)
then it can be
argued that the system may display instability. If the parameter a is positive, but there is a tendency
for its reduction, then we can assume that the system is approaching the
disaster. In both cases, it is necessary to continue studying the system and
identify the conditions or possible timing of the disaster, assess its likely
consequences. If by the level of determination, the level of significance of
the regression equation of one of the disasters exceeds the regression equation
of relations of a stable nature, then a catastrophe should be considered as
possible.
Public
Company "Motor Sich", which is engaged in
development, production, repair and service of aviation gas turbine engines for
airplanes and helicopters, was chosen as an object of analysis (KASIANOVA,
KAVUN 2018). On the basis of the analysis of economic performance of the
enterprise, its stability is assessed (Table 2).
The given indicators allow to conclude, about positive tendencies of
functioning of the enterprise. Statistical analysis has shown that the most
significant factor in assessing the sustainability of an enterprise is the
importance of the ratio of current liquidity.
Table 2: Dynamics of development of Public Company "Motor Sich" for 2006-2017.
|
|
Cost of assets, UAH thou. |
Sales revenue, UAH thou. |
Net profit, UAH thou. |
Cost of sales, UAH thou. |
EBITDA margin,% |
Current liquidity |
|
2006 |
2267439 |
1278964 |
37627 |
762639 |
15,70 |
1,500 |
|
2007 |
2924979 |
1800852 |
216263 |
984263 |
22,17 |
1,725 |
|
2008 |
3537314 |
2131572 |
3843 |
1326556 |
17,14 |
1,432 |
|
2009 |
4210663 |
3837706 |
754646 |
2137504 |
31,88 |
1,977 |
|
2010 |
6141903 |
5106758 |
1248028 |
2666560 |
34,17 |
2,043 |
|
2011 |
8182339 |
5891225 |
1344161 |
2927924 |
38,77 |
2,294 |
|
2012 |
11712209 |
7845558 |
1822865 |
4628489 |
42,17 |
2,805 |
|
2013 |
13196110 |
8583924 |
1319191 |
4974227 |
36,46 |
3,262 |
|
2014 |
16584942 |
10730122 |
1560367 |
5514991 |
53,81 |
2,784 |
|
2015 |
20756541 |
13830655 |
3399842 |
4907340 |
69,60 |
2,786 |
|
2016 |
25251032 |
10546323 |
2044097 |
4137864 |
41,73 |
3,197 |
|
2017 |
29243457 |
15150429 |
3104174 |
6687998 |
42,18 |
3,531 |
Source: authors' calculations
According
to the initial data of economic indicators for 12 years, the most deterministic
model of enterprise development has been obtained, which has the form:
(9)
For a negative value of the parameter a, the function described by the
equation is a nonmonotone function. The function of
enterprise development will reach the point of extremum (points of unstable
equilibrium) at x=2,201.
Since the model disaster Public Company "Motor Sich" is determined in relation to the model of the
enterprise, it can be concluded on sustainable development for the period
2006-2017 years. That is the economic condition of Public Company "Motor Sich" can be described as stable. By calculating the
corresponding regression equations for other parameters, it is possible to
determine the possible changes of the resulting indicator when individual
factors change in the direction of increase or decrease. At the same time, it
is impossible to assess the changes in the development of the enterprise, since
the scale of the indicator of development, which is analyzed, varies from
catastrophic to excellent within the "one step" (with a change in the
ratio of current liquidity by 50% in one direction or the other).
Using the Maple 18 program, two types of model
calculations were carried out for Public Company "Motor Sich" without external interference and using chaos
management in a particular case presented by the model (7). For each
calculation were taken four different initial state of the system. For the
first model (Figure 2), the development of an enterprise leads to a stable
attractor with coordinates (x = 1,12;
s = 0,73). Managed chaos shifts the trajectory of enterprise
development into another stable attractor (Figure 3) with a lower level of
development and approximately the same level of chaos (x = 0,83; s = 0,42). In cases of chaos management,
approaching a new attractor is faster than with the natural development of the
economic system.
|
|
|
|
Figure 2. The behavior
of the system in natural conditions |
Figure 3. The behavior
of the system in a controlled chaos |
Thus, in economic systems, including microeconomic ones,
which are complex by their nature, chaos management remains a global problem.
the problem of forming a complex of management measures requires further
research.
5. CONCLUSIONS.
The practical application of the elements of the chaos
theory allows us to assess the possible changes in the sustainability of
enterprise development by increasing entropy, as well as to identify the main
positive trends in the change of indicators to improve the stability of the
enterprise in terms of uncertainty. But the steady development of the company
today can not guarantee the absence of disasters
tomorrow. Any insignificant controlling influence can lead to the loss of an
enterprise balance.
In turn, the implementation of chaos-based controlled
chaos strategy implies a certain "chaosification"
of the system in a controlled manner, which will allow for prediction of
possible disturbances and prepare the system for the transition to a new
development trajectory at the optimal time with minimal losses. Thanks to chaos
engineering, you can achieve a deeper vision of the effects of chaos in order
to improve the stability of the system. This, ultimately, is the basis for
creating more mature and reliable systems that can recover and reduce harm in
the event of a serious security incident.
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