Volume 03 Issue 07-2023
140
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
03
ISSUE
07
Pages:
140-145
SJIF
I
MPACT
FACTOR
(2021:
5.478
)
(2022:
5.636
)
(2023:
6.741
)
OCLC
–
1368736135
A
BSTRACT
Currently, obtaining reliable data and its quick analysis has become the most important condition for
successful management. This is especially true if the object of management and its external environment
are a set of complex processes and factors that significantly influence each other. One of the most effective
ways to solve problems arising in the field of management and organization is the use of cognitive modeling
in the digital economy, which is the subject of study in this article.
K
EYWORDS
Digital economy, digital business, modeling, cognitive model, measurement factor, cognitive analysis,
alternative solution, business process management, management decisions, analytical software, services
based on cognitive computing, transactions, blockchain.
I
NTRODUCTION
Cognitive modeling is used to systematize,
analyze and make management decisions in
complex and uncertain situations (geopolitical,
domestic, military, etc.), in the absence of
Journal
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Research Article
THE IMPORTANCE OF COGNITIVE MODELING IN THE
DIGITAL ECONOMY AND COGNITIVE SYSTEMS AND SERVICES
IN DIGITAL BUSINESS
Submission Date:
July 20, 2023,
Accepted Date:
July 25, 2023,
Published Date:
July 30, 2023
Crossref doi:
https://doi.org/10.37547/ijasr-03-07-25
Ravshan Abduraxmanov
Doctor Of Philosophy In Technical Sciences, Associate Professor Of Jizzakh Branch Of The National
University Of Uzbekistan
Murotjonova Mubina Dilshod Qizi
Jizzakh Branch Of The National University Of Uzbekistan Named After Mirzo Ulugbek, Faculty Of
“Psychology”, 5230100
- Economy (By Industries And Sectors), Student Of Group 140-20 Uzbekistan
Volume 03 Issue 07-2023
141
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
03
ISSUE
07
Pages:
140-145
SJIF
I
MPACT
FACTOR
(2021:
5.478
)
(2022:
5.636
)
(2023:
6.741
)
OCLC
–
1368736135
quantitative or statistical information about the
processes taking place in such situations.
intended. Cognitive modeling helps to better
understand the problem situation, identify
contradictions and qualitatively analyze the
system. The purpose of modeling is to formulate
and clarify hypotheses about the operation of the
object in question as a complex system consisting
of interrelated elements and subsystems. The
emergence of the cognitive approach is related to
the complexity of analysis and decision-making in
fields such as economics, sociology, and ecology.
In such systems, the number of factors that need
to be taken into account when making a decision
is measured by dozens. The factors themselves
have a complex interaction. Often, there is no
specific
methodology
for
determining
measurement factors, and the amount of data is
insufficient or qualitative in nature. Due to the
specific characteristics of such systems, they are
called weakly structured.
One of the definitions of common cognitive
modeling is the following definition - it is a
method of analysis with the ability to determine
the strength and direction of the influence of
factors in making the management object a target,
taking into account the similarities and
differences of the influence of various factors on
the management object. Cognitive modeling helps
to better understand the problem situation based
on the qualitative analysis of the system. It allows
you to identify problems and contradictions
specific to the system. The purpose of modeling is
to form and clarify a hypothesis about the
operation of the object under study, which is
considered as a complex system consisting of
separate, but interrelated elements and
subsystems.
Cognitive analysis of the research object allows
you to:
•
to see the general situation of the analyzed
problem;
•
prediction of system (situation) development
direction;
•
to determine the factors affecting the
development of the situation;
•
development of action strategy;
•
offer alternative solutions to the problem;
•
formation of the decision-making process;
•
obtaining qualitative and quantitative
descriptions
of
the
situation
under
consideration;
•
increase the quality and validity of decisions.
•
The step-by-step technology of cognitive
analysis includes the following steps:
•
collecting preliminary information about the
problem;
•
systematic study of the problematic situation
(the problem is permanent or changing in
nature);
•
structure of knowledge on the subject of the
problem;
•
create a cognitive model of the studied
problem;
•
structural analysis of the cognitive problem
situation;
•
structural features of the cognitive model of
the problem situation;
Volume 03 Issue 07-2023
142
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
03
ISSUE
07
Pages:
140-145
SJIF
I
MPACT
FACTOR
(2021:
5.478
)
(2022:
5.636
)
(2023:
6.741
)
OCLC
–
1368736135
•
problem modeling based on a target
approach;
•
possible results at the model level, denial of
current models;
•
thematic interpretation of modeling results;
•
to analyze the results and determine new
knowledge about the dynamics of the
situation.
The essence of the cognitive approach is to
develop an effective management strategy based
not on intuition, but on organized and verified
information about a complex system.
The source of such knowledge can be sociological
research of the population or surveys of expert
groups. The development of cognitive models is a
very laborious process, so special tools are
needed to automate the work of researchers.
The tools of cognitive technologies are diverse
and they are designed to solve different
problems:
•
business process management;
•
supporting management decisions;
•
analytical software and services;
•
services based on cognitive computing;
•
transactions and blockchain.
When talking about cognitive systems and
services in digital business, it can be said that a
natural cognitive system is a biological system of
cognition based on the consciousness of a living
organism (individual, group, community). The
basis of such a cognitive system is the interaction
of thinking, consciousness, memory and language.
Although it is not clear in the general case, it is
possible to agree with the opinion that the human
brain is the main carrier of the cognitive system.
An artificial cognitive system is a non-biological
system characteristic of machines with features
of artificial intelligence with cognitive functions
and the ability to connect time to create an
interactive temporal model of events.
Modern mental systems use communication
technology, cognitive models, and computer
systems to transform raw data into useful
information for business analysis and decision-
making. The tools used include intellectual and
textual analysis of data, operational-analytical
processing aimed at processing a large amount of
unstructured data. It helps identify new strategic
business opportunities and allows for more
accurate alignment of existing business
processes.
Cognitive business analytics (CBA) can be used to
support a wide range of business objectives and
strategies. Short-term operational solutions such
as product placement and competitive pricing
have greatly expanded with CBA. Long-term
strategies in areas such as brand recognition and
market share will be more successful with the
forecasting and scene modeling that CBA
provides. An important advantage of cognitive
systems in general, and CBA systems in particular,
is that they have the ability to process both
external information from the market in which
the company operates, and internal information
from the company, such as financial indicators
and operational data. When external and internal
information are combined, they will create
knowledge in the future that cannot be obtained
Volume 03 Issue 07-2023
143
International Journal of Advance Scientific Research
(ISSN
–
2750-1396)
VOLUME
03
ISSUE
07
Pages:
140-145
SJIF
I
MPACT
FACTOR
(2021:
5.478
)
(2022:
5.636
)
(2023:
6.741
)
OCLC
–
1368736135
in any other way. Technological and
methodological provision of cognitive systems for
business is aimed at supporting knowledge about
previous, current and forecast indicators, ideas
and its status.
Depending on the needs, the following
capabilities and technologies of business analysis
can be used:
•
BI - reporting (reporting based on business
intelligence systems);
•
Data Mining (intelligent information search);
•
Intellectual processing of complex events;
•
CPM (application programs for managing
business activities);
•
Comparison based on expert systems.
In the field of financial services, cognitive systems
are used in order to optimize the process of risk
management,
prepare
personal
recommendations and potential objects for
investments, evaluate financial data of the stock
exchange and information about customers.
Predictive models built on platforms and their
cognitive capabilities help to identify the most
profitable and actively developing business lines
and help clients increase their return on
investment. Other tasks include financial risk
modeling and detection of money laundering and
suspicious transactions. In the banking sector, as
well as in other sectors, where processing of large
volumes of data and personalized service is
important, cognitive systems will fundamentally
change the relationship between banks and
customers. Machine learning and user behavior
analysis allow us to identify some important
patterns and trends, predict expected customer
behavior, create personalized offers for
customers, and improve service quality. In
addition, cognitive systems are used to detect
fraud, analyze and automate threats, as well as
develop recommendations.
The main goal of cognitive management
technologies is to support decision-making that
helps reduce operating costs, increase revenue,
increase competitiveness, improve the efficiency
of almost any business, or simply get advice on
request. In the near future, with the development
of cognitive technologies, the principles of
working with information will change, just as
personal computers have changed their lives in
time. Based on the accumulated knowledge about
the system, the assistants can give reasonable
advice on the feasibility of completing a specific
business issue, developing a sequence of its
elimination, monitoring its implementation, and
determining priorities in the execution of work.
Business success in modern conditions is
provided by the hardware capabilities of
information technologies - the speed of
infrastructures and communication channels, as
well as cognitive technologies used in the
development of the most interesting and
promising offers on the market and data analysis.
Modern business processes continue to become
more complex, and the time to make important
decisions in the company's operation is running
out. Companies that have found their niche are
slowly expanding, but as they scale, most of them
realize that no single person or team is enough to
handle the amount of data they face today.
Volume 03 Issue 07-2023
144
International Journal of Advance Scientific Research
(ISSN
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2750-1396)
VOLUME
03
ISSUE
07
Pages:
140-145
SJIF
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FACTOR
(2021:
5.478
)
(2022:
5.636
)
(2023:
6.741
)
OCLC
–
1368736135
Analytics, artificial intelligence, clouds, enterprise
mobility, blockchain and other latest technologies
are helping not only large corporations, but also
small companies. And these processes determine
the digitization of business.
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