Industry 4.0 technologies as a factor in economic development
The article explores the potential of Industry 4.0 technologies as a factor in the development of the economic system. It analyzes the key technologies of the Fourth Industrial Revolution, namely Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, and 3D printing, and their impac...
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| Опубліковано в: : | Економічний вісник Донбасу |
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| Дата: | 2024 |
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| Формат: | Стаття |
| Мова: | Англійська |
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Інститут економіки промисловості НАН України
2024
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| Онлайн доступ: | https://nasplib.isofts.kiev.ua/handle/123456789/203370 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | Industry 4.0 technologies as a factor in economic development / O. Serdiuk // Економічний вісник Донбасу. — 2024. — № 4 (78). — С. 19-25. — Бібліогр.: 9 назв. — англ. |
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Digital Library of Periodicals of National Academy of Sciences of Ukraine| _version_ | 1860122348149014528 |
|---|---|
| author | Serdiuk, O. |
| author_facet | Serdiuk, O. |
| citation_txt | Industry 4.0 technologies as a factor in economic development / O. Serdiuk // Економічний вісник Донбасу. — 2024. — № 4 (78). — С. 19-25. — Бібліогр.: 9 назв. — англ. |
| collection | DSpace DC |
| container_title | Економічний вісник Донбасу |
| description | The article explores the potential of Industry 4.0 technologies as a factor in the development of the economic system. It analyzes the key technologies of the Fourth Industrial Revolution, namely Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, and 3D printing, and their impact on economic processes. Special attention is given to the role of Artificial Intelligence, which is the main driver of the transformation of production processes. The possibilities of production automation through AI, its ability to analyze real-time data, manage resources, and optimize production processes are examined. It is established that the implementation of AI contributes to reducing operational costs, improving product quality, and more efficient resource utilization. The Internet of Things is considered as a technology that enables the integration of production processes and communication between devices in real-time. Emphasis is placed on its role in the formation of "smart factories" and the transition to a "pull economy" model, which allows manufacturers to quickly adapt to changes in consumer demand. Blockchain technology is studied in the context of reducing transaction costs and ensuring the transparency of economic relations. The prospects for the use of smart contracts in logistics, finance, and business process management are analyzed, along with potential threats related to the centralization of control over data. 3D printing is considered as a tool for optimizing production processes and personalizing products.
В статті розглянуто потенціал технологій Індустрії 4.0 як фактора розвитку економічної системи. Проаналізовано ключові технології Четвертої промислової революції, зокрема Штучний інтелект (ШІ), Інтернет речей (IoT), блокчейн та 3D-друк, і їхній вплив на економічні процеси. Особливу увагу приділено ролі Штучного інтелекту, який є основним рушієм трансформації виробничих процесів. Досліджено можливості автоматизації виробництва за допомогою ШІ, його здатність до аналізу даних у реальному часі, управління ресурсами та оптимізації виробничих процесів. Встановлено, що впровадження ШІ сприяє зниженню операційних витрат, покращенню якості продукції та ефективнішому використанню ресурсів. Розглянуто Інтернет речей як технологію, що забезпечує інтеграцію виробничих процесів і комунікацію між пристроями в режимі реального часу. Наголошено на його ролі у формуванні "розумних фабрик" та переході до моделі "витягаючої економіки", яка дозволяє виробникам швидко адаптуватися до змін у споживчому попиті. Технологія блокчейн досліджується в контексті зниження трансакційних витрат та забезпечення прозорості економічних відносин. Аналізуються перспективи застосування смарт-контрактів у логістиці, фінансах та управлінні бізнес-процесами, а також потенційні загрози, пов’язані з централізацією контролю над даними. 3D-друк розглядається як інструмент для оптимізації виробничих процесів та персоналізації продукції.
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| first_indexed | 2025-12-07T17:39:53Z |
| format | Article |
| fulltext |
O. Serdiuk
19
Економічний вісник Донбасу № 4(78), 2024 ISSN 1817-3772
DOI: https://doi.org/10.12958/1817-3772-2024-4(78)-19-25
UDC 338.2:004.8
O. Serdiuk,
DrHab (Economics), Senior Researcher,
ORCID 0000-0003-3049-3144,
e-mail: serdyuk_O@nas.gov.ua,
Institute of Industrial Economics of NAS of Ukraine, Kyiv
INDUSTRY 4.0 TECHNOLOGIES AS A FACTOR
IN ECONOMIC DEVELOPMENT
Introduction. Economic development is
inextricably linked to the introduction of new
technologies that improve production processes,
resource management, and business organization.
However, the scale and nature of this impact vary
significantly depending on the industry, region, and
level of technological system integration in production,
leading to ambiguous consequences for the economy.
Given this, it becomes relevant to study the economic
effects of the widespread adoption of Industry 4.0
technologies, such as artificial intelligence (AI), the
Internet of Things (IoT), blockchain, and 3D printing.
As Klaus Schwab notes, we are currently in the era
of the Fourth Industrial Revolution, which involves
transitioning industrial production to the Industry 4.0
model. In his key works, The Fourth Industrial
Revolution [1] and Shaping the Future of the Fourth
Industrial Revolution [2], he focuses on the production
and social implications of this process. However, the
issue of structural changes in the economic system due
to the influence of Industry 4.0 technologies remains
insufficiently explored. This highlights the need for
further research in this area.
The purpose of this article is to determine the
consequences of Industry 4.0 technologies on the
economic system.
Research Results. The key technologies of the
Fourth Industrial Revolution include artificial
intelligence, the Internet of Things, 3D printing, and
blockchain. Each of them influences specific aspects of
production activities while also indirectly affecting the
economic system as a whole. Their combined use
amplifies their impact, enhancing efficiency in
industrial applications and transforming social
mechanisms.
Artificial intelligence (AI) is the most influential
technology in both the production and social spheres. AI
is a digital technology designed to perform complex and
diverse tasks traditionally requiring human intelligence.
According to interdisciplinary research in cognitive
sciences, mathematics, computer technology, neuro-
science, and philosophy, AI is classified into three
levels:
Narrow AI – Systems specialized in solving
specific tasks and capable of performing only a limited
number of functions.
General AI – A hypothetical system capable of
performing any intellectual tasks inherent to humans. It
can learn, reason, adapt to new situations, and solve
problems across various domains.
Superintelligence – A hypothetical system that
surpasses human intelligence in all aspects.
Currently, only the first level of AI exists.
However, even its limited functionality has been
sufficient to initiate fundamental changes in production
models and social relations. To determine the structure
and assess the scale of these changes, it is necessary to
study the areas of AI application and evaluate its local
impacts.
First and foremost, attention should be given to the
general industrial aspect of AI application – its
functionality, which, with certain variations, can be
relevant to most types of industrial enterprises. The most
effective use of AI in this context lies in the automation
of production processes through robotics controlled by
AI. This functionality enables continuous, round-the-
clock production while minimizing the involvement of
workers engaged in routine tasks. An additional
advantage is that AI algorithms efficiently perform
quality control tasks and can optimize production
processes by reducing errors. As a result, operational
costs decrease due to reduced manual labor, while the
rational use of materials and resources contributes to
lowering overall production expenses.
Another effective general industrial function of AI
is resource planning and management. The principle of
this functionality is that AI algorithms, based on the
analysis of retrospective and real-time data, calculate
optimal solutions for supply chain organization,
inventory management, production planning, and
workforce allocation. This helps minimize transaction
costs, including expenses related to partner searches,
inventory control, and production process coordination.
As a result, overall production costs are reduced,
positively impacting the profitability of the enterprise.
Another important AI function from a cost-saving
perspective is energy consumption optimization. This
© Publisher Institute of Industrial Economy of National Academy of Sciences of Ukraine, 2024
© Publisher State Higher Education Institution "Luhansk Taras Shevchenko National University", 2024
O. Serdiuk
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ISSN 1817-3772 Економічний вісник Донбасу № 4(78), 2024
effect is achieved through analyzing energy
consumption data at each stage of the production
process, from equipment startup to product completion.
Based on this analysis, AI algorithms can identify peak
loads, reduce energy losses, and find ways to use
equipment more efficiently. For example, AI can
optimize machine operating times to prevent power grid
overloads or redistribute tasks to lower energy
consumption during peak hours. Implementing such
functionality significantly reduces energy costs and
enhances overall production efficiency.
In the context of sectoral improvements, the
following AI functions should be highlighted:
Manufacturing of new products in the mechanical
engineering sector, such as autonomous vehicles.
Optimization of chemical reactions through
modeling in chemical production.
Quality control of metals using AI-powered
image analysis systems in metallurgy.
Optimization of energy equipment performance
and management of smart grids in the energy sector.
Personalized product design (customized based
on customer requests) in the textile industry.
Development of new drugs through disease data
analysis in pharmaceuticals.
Project planning and the use of robots in
construction for building projects.
All these sectoral applications complement the
general (universal) advantages of AI, making it an
effective tool for improving production quality and
profitability. Despite its obvious technical advantages,
the economic feasibility of AI implementation in
production is not always justified. The high cost of
equipment and long payback periods may lead
entrepreneurs to prefer human labor, especially in
countries where labor costs are low. Even in wealthier
countries, long-term AI adoption may present
challenges. Based on economic theory, it can be
predicted that, initially, high labor costs in these
countries will encourage businesses to replace human
workers with AI-driven automation. However, after
mass layoffs of low-skilled workers, the cost of labor in
the market will decrease, making AI-based automation
less attractive to investors – as hiring human workers
will once again become more cost-effective.
To sustain the dynamic development of AI-based
production, governments of developed countries may
implement several measures. In particular, they could
introduce progressive taxation to increase the volume of
social benefits, which may reduce the dependence of
low-income groups on low-paid jobs. This, in turn,
would encourage workers to demand higher wages.
Additionally, governments could invest more funds in
education, which would potentially reduce the number
of low-skilled workers, thereby increasing their market
value. Furthermore, quality, safety, and production
control standards could be introduced at the national
level, making routine tasks performed by low-skilled
workers less competitive compared to automated AI
solutions.
However, the current cost of AI-powered
equipment is not fixed. Several factors have already
contributed to its cost reduction, and this process is
likely to continue. The primary reason for this is the
declining cost of semiconductor production, which is
explained by Moore’s Law [3]. According to this law,
the number of transistors on an integrated circuit
doubles approximately every two years, leading to
exponential performance growth and a reduction in
computing power costs per unit. Although the effect of
Moore’s Law has slowed somewhat in the 2020s, its
impact is being sustained through new approaches, such
as the introduction of 3D chips and optimization of
semiconductor architectures.
Another important factor that may contribute to the
cost reduction of AI equipment in the future is the
increase in competition within this industry. As demand
for such equipment grows, new manufacturers are
expected to enter the market, while existing companies
will be forced to introduce innovations to maintain their
market positions. This market dynamic will not only
improve equipment quality (e.g., increasing
performance or energy efficiency) but will also lower
costs, as increased supply will naturally drive prices
down.
At the same time, software-related factors play a
crucial role, as they directly impact the efficiency of AI
hardware and, consequently, its economic viability.
Innovations in AI algorithms, particularly in machine
learning and deep learning, significantly optimize
computational processes, reducing hardware resource
requirements. New algorithms, better adapted to
specific tasks, can greatly reduce the need for high-
performance computing systems for complex opera-
tions. As a result, the demand for high-end hardware
decreases, lowering development and operational costs.
Moreover, the integration of software solutions for data
processing and access optimization helps reduce the
load on hardware components. Collectively, all these
factors contribute to the overall reduction in the
maintenance costs of AI-driven management systems.
If the above-mentioned factors contributing to the
cost reduction of AI equipment are confirmed, we can
expect a rapid increase in the share of AI-driven
production in the near future. This trend will primarily
affect developed economies, where high labor costs,
innovation-driven competition, and stringent quality
standards will encourage entrepreneurs to replace low-
skilled workers (and, in some cases, even highly skilled
professionals) with AI-based equipment. Under these
conditions, the structure of the economy will largely
depend on the domestic policies of each government. If
a government implements social support programs for
low-income groups, funded by wealthier citizens
(including through progressive taxation), a significant
portion of low-skilled workers who lost their jobs due to
O. Serdiuk
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Економічний вісник Донбасу № 4(78), 2024 ISSN 1817-3772
AI adoption in enterprises may remain outside economic
processes. In this scenario, they would rely on social
benefits instead of contributing to economic
development. However, if the government does not
provide special support to low-income groups, it is
highly likely that most displaced workers will find
employment in the service sector, which will expand
due to the overall economic growth driven by AI
technologies in production.
From the perspective of overall economic
development, the second scenario is more promising.
Competition in AI-powered production should lead to
an increase in the supply of consumer goods, thereby
reducing their prices. This, in turn, will enhance the
purchasing power of the population, with some of that
increased spending redirected toward the service sector.
As a result, demand for services will grow, stimulating
capital inflows and labor absorption in this sector.
Ultimately, the economy will expand, and citizens will
gain access to a broader range of goods and services.
Based on its impact on the economy, AI can be
classified as a disruptive technology. Similar to the
technologies analyzed by Carlota Perez [4], AI has
already partially realized its potential for structural
transformations within the economic system. Today,
new types of production exist (e.g., autonomous drones
and vehicles, household robots, AI-driven systems)
along with new labor organization models (e.g., hybrid
workplaces, robotic production lines, autonomous
logistics systems) – all of which were unknown twenty
years ago. Additionally, a new infrastructure has been
created to support AI development, including data
centers, cloud computing platforms, and more. All these
factors indicate that AI meets the criteria defining
technologies capable of initiating technological
revolutions, according to Carlota Perez’s theory. It can
be assumed that if she were writing her work today, a
new concept – the "Sixth Technological Revolution" –
would likely emerge.
It is also important to note that, similar to other
disruptive technologies described by Carlota Perez, AI
drives the development of numerous complementary
innovations, which, in turn, Klaus Schwab has identified
as the "pillars" of the Fourth Industrial Revolution. One
of the most prominent of these is the Internet of Things
(IoT) – a network of internet-connected physical devices
that automatically collect, transmit, and exchange data
without human intervention. These devices are equipped
with sensors, software, and communication modules,
enabling them to interact both with each other and with
other systems via the internet. AI’s role within the IoT
is to process real-time data, identifying patterns upon
which production decisions are made. Furthermore, AI
implements algorithms that enable the automatic
execution of these decisions.
The Internet of Things (IoT) driven by AI
(Intelligent Internet of Things) is one of the key
technologies of the Smart Factory. This concept
involves the creation of a fully integrated, automated,
and self-learning environment that ensures high
productivity and efficiency in manufacturing processes.
This result is achieved by reading large datasets from
manufacturing devices and processing them, based on
which AI algorithms make optimal production decisions
and implement them in the physical environment.
Workers at smart factories focus on system setup,
quality control, and occasionally make complex
strategic decisions.
One example of a smart factory is the Siemens
plant in Amberg, Germany, which specializes in
electronics manufacturing. It uses advanced AI-
controlled robotic production systems via IoT
infrastructure. Around 75% of all processes at the
factory are automated, leading to significant resource
savings and productivity gains. Similarly, German
BMW factories use AI and IoT infrastructure to
automate the assembly of cars.
It is also worth noting the sectoral aspects of IoT
applications. In particular, this technology is used in
agriculture for monitoring soil moisture and
temperature. In energy – for collecting information on
electricity consumption, based on which its distribution
is optimized. In metallurgy – for detecting defects in
furnaces, rolling mills, and other equipment. In the
chemical industry – for tracking production parameters
such as temperature, pressure, and substance
concentration. And in many other sectors as well.
However, the global impact of IoT on the economy
is not limited to just efficient manufacturing. The
communication capabilities created by this technology
lead to a transformation in the model of relations
between producers and consumers in the market. By
providing a connection between physical devices
(production equipment), digital platforms (market-
places), and consumers, IoT enables manufacturers to
collect real-time data on product sales, analyze it, and
quickly adjust production processes to meet changing
demand. At the same time, IoT helps manufacturers
"stay ahead of the curve" by providing the ability to
analyze consumer preferences (such as browsing history
or views of specific products), allowing them to create
personalized products and offers.
The economic effect of collecting information
through IoT is enhanced when this data is directed to
"smart factories." At such enterprises, AI analyzes the
received data and adjusts production processes
according to current demand. This helps avoid
overproduction, minimize waste, and optimize costs.
The demand and supply principle shaped by IoT
leads to a shift in the economic system toward the model
of the so-called "pull economy." This model is based on
meeting actual consumer demand through the fastest
and most accurate response to market requests. Today,
most market segments operate under the traditional
"push economy" model, where products are made based
on demand forecasts. In contrast, within the "pull
economy" model, production only begins when a real
request from a specific consumer is made. This model is
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characterized by the absence of overproduction and
excessive stockpiling of resources.
However, according to some scholars, the "pull
economy," based on demand and supply signals
transmitted through IoT infrastructure, threatens to
cause an asymmetric redistribution of societal resources
in favor of those who collect digital information.
Professor Shoshana Zuboff of Harvard Business School
described this phenomenon as "surveillance capitalism"
[5]. Its essence lies in the collection, analysis, and
monetization of users' personal data from digital content
without their conscious consent. This data is used to
develop predictive models and influence people's
behavior, turning their actions and emotions into
commodities. The system created in this way generates
asymmetry of knowledge and power between
technological corporations and society, violating
privacy and freedom. In this context, Zuboff criticizes
corporations like Google and Facebook for their data
monetization practices, such as creating personalized
advertisements and predicting consumer behavior. In
her view, this enables tech companies to influence
societal behavior for profit.
Despite the validity of the problem of "surveillance
capitalism" caused by the use of the Intelligent Internet
of Things, the paradigm of Industry 4.0 itself holds
potential for partial resolution. This refers to data
protection mechanisms using blockchain technology,
which ensures decentralized data storage in the form of
sequential and immutable records in a register (blocks)
linked in chronological order. Through blockchain,
consumers will be able to interact directly with
manufacturers, reducing the involvement of third-party
internet services (browsers, centralized digital
platforms), thus reducing the risks of data collection by
third parties. Furthermore, within this new
communication model, manufacturers will only have
access to the data necessary for fulfilling current orders,
limiting the possibilities for gathering additional data
about consumers. As a result, secondary data will
become less accessible to businesses, thus limiting
opportunities for monetizing it.
Strengthening the protection of data for economic
agents is just one of the advantages provided by
blockchain. In addition, the technology can contribute to
reducing transaction costs related to accounting,
auditing, counterparty verification, payments, and so on
[6]. The mechanism for this reduction lies in the use of
distributed ledgers as a source of reliable information,
which is extremely difficult for third parties to alter.
This information can include records of payments made,
obligations of economic agents, movement of goods,
and more. Thus, once data is recorded in the blockchain,
it remains immutable, reducing the need for repeated
verification of its authenticity. This helps save time and
resources for economic agents, thereby reducing
transaction costs in their activities. For example, by
recording information about a money transfer for goods
delivered in the blockchain, the parties to the agreement
will not need to involve a third party (such as a bank) to
complete the transfer. Instead, cryptocurrency, with
significantly lower transaction costs, will be transferred
to the seller's account, making the transaction more
economically efficient for both parties.
The successful integration of blockchain
technology with fundamental software solutions opens
up opportunities for even further reduction of
transaction costs in economic activities. In this context,
it is worth noting smart contracts as part of the
blockchain ecosystem, which automatically execute the
terms of an agreement between parties without the need
for intermediaries. The principle behind their operation
is that the contract terms, in the form of code, are
recorded in the blockchain, making them immutable.
After that, the system waits for a signal indicating that
one part of the agreement has been fulfilled, and upon
receiving this signal, it automatically executes the other
part. For example, when entering into a supply
agreement, the entrepreneur transfers the required
amount of funds or digital assets into the smart contract,
where they are reserved. After the delivery of the
product is confirmed, the system automatically transfers
the funds to the supplier’s account, eliminating the need
for additional verifications and intermediaries.
An analysis of blockchain's potential shows that,
unlike other Industry 4.0 technologies that influence the
economic system through the optimization of
production processes and simplified communication,
blockchain primarily transforms institutions. Moreover,
this transformation occurs from the bottom up-driven by
objective economic realities. In other words, economic
agents find new, more effective mechanisms for
protecting personal information, ensuring contract
terms, and handling material transactions, while
governments, in turn, respond to such changes
retroactively. The response of regulatory bodies can
vary, from adapting legislation to new forms of
interaction between economic agents, to outright
banning alternative informal institutions that have been
built around the technological capabilities created by
blockchain.
Although the institutions created under the
influence of blockchain offer clear advantages in the
form of lower transaction costs in economic activities, it
cannot be confidently expected that governments will
take measures to legalize them. In this case, much
depends on various factors, including the political
climate, the pluralism of the political system, the
structure of financial flows, and the level of their
concentration in the hands of certain influential entities.
For example, in a country where the ruling party or
president is funded by a group of people profiting from
the banking business, it is unlikely that cryptocurrency
payments will be legalized. On the other hand, in
countries with less concentrated financial flows and a
competitive political system, there is a higher likelihood
that laws will be passed to formalize effective
institutions. Thus, the ruling party or president will
O. Serdiuk
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Економічний вісник Донбасу № 4(78), 2024 ISSN 1817-3772
likely try to gain voter support to extend their time in
power.
Similar motivations may drive political
influencers, either restraining or encouraging the
adoption of other Industry 4.0 technologies. In
particular, regarding the disruption of established
economic relations, the impact of 3D printing on rent
distribution structures should be noted. This technology
allows for the creation of three-dimensional objects by
layer-by-layer deposition of material based on a digital
model. Unlike traditional production methods, such as
casting or milling, 3D printing enables the production of
complex parts without the use of expensive molds and
unnecessary material costs. The main stages of
production using 3D printing include:
1. Creating a 3D model – the object is initially
modeled in special programs (e.g., AutoCAD, Blender,
SolidWorks).
2. Slicing the model into layers – the 3D printing
software (e.g., Cura, PrusaSlicer) divides the model into
individual layers for printing.
3. Printing layer by layer – the printer sequentially
applies material until the finished object is formed.
Thus, production occurs without the use of
traditional bulky equipment, parts, and components,
which deprives the manufacturers of these components
of their earnings. In particular, this affects producers of
products for the aviation, automotive, construction,
textile, food, and jewelry industries. Losses also
threaten businesses that continue to use traditional
production methods as opposed to 3D printing.
In cases where political influencers receive rents
from industries that may incur losses due to the spread
of 3D printing technology, it can be expected that they
will oppose these innovations. For example, they might
lobby for high import tariffs on 3D printers or their
components, officially justifying this as a necessity to
protect domestic producers. Conversely, if influential
agents are interested in the development of
manufacturing sectors that will benefit from 3D
printing, they will promote the adoption of this
technology.
From a purely economic perspective, 3D printing
technology reduces the value creation chain while not
diminishing the value and quality of the product. This
aspect influences the acceleration of production speeds
and the reduction of product costs, making it more
accessible to consumers. Furthermore, 3D printing
allows for the optimization of resource use, reducing
waste levels compared to traditional manufacturing
methods, which helps decrease raw material costs and
environmental impact.
Just as conveyor belt manufacturing once displaced
manual assembly, initiating the era of mass
consumption, 3D printing, in combination with
Artificial Intelligence and the Internet of Things, can
fundamentally transform modern production processes,
ushering in the era of customized consumption.
The concept of customized consumption represents
a systemic approach to adapting products and services
to the individual needs and preferences of consumers. It
involves actively engaging buyers in the product
creation process, allowing it to align with their
expectations. From the perspective of production-
consumption relationships, customized consumption is
a logical extension of the principles of the "pull
economy" and is effectively implemented in the context
of smart factories. In such conditions, production
processes become more flexible, automated, and
focused on personalized demand, while technological
solutions such as digital twins, artificial intelligence,
and big data analytics ensure the rapid adjustment of
production capacities to dynamic consumer preferences.
Based on the results of the study of the impact
mechanisms of Industry 4.0 technologies on economic
processes, it can be concluded that, with widespread
implementation, these technologies could significantly
alter the structure of the economic system, influencing
its key characteristics: what to produce, how to produce,
and for whom to produce. The potential driver of change
in this case is the functionality of fast and almost lossless
data exchange, managed by Artificial Intelligence. For
instance, the integration of AI with 3D printing
technology allows for the transmission of data about the
properties of products to a 3D printer, which
automatically and with minimal maintenance costs
carries out the production process. The speed of data
transmission and the production versatility of the 3D
printer open up possibilities for manufacturing
personalized products, stimulating the transition of the
economic system to customized production. Along with
this, the symbiosis of these factors contributes to the
autonomy and localization of production processes,
affecting the shortening of the value creation chain.
Decentralized storage of cryptographically
protected and immutable data via blockchain opens up
opportunities to reduce transaction costs for institutions
that facilitate interactions between economic agents. In
particular, the implementation of a digital business
registration system at the state level based on blockchain
will reduce bureaucratic barriers, ensure transparency of
procedures, and, through data processing automation,
significantly accelerate the registration process. A
successful example of such a system is Estonia's e-
Residency program, which enables non-residents to
register a business, sign documents, and manage a
company online. However, the program does not
provide tax residency or the right to reside in Estonia
[7].
In the context of reducing transaction costs for
institutions that facilitate the interaction of private
entrepreneurs, digital smart contract services –
developed on the basis of blockchain – are highly
effective. They contribute to reducing costs associated
with: verifying the fulfillment of contract terms; the
need for intermediaries; risk management; document
circulation; and communication. This effect is achieved
O. Serdiuk
24
ISSN 1817-3772 Економічний вісник Донбасу № 4(78), 2024
through the transparency and immutability of the data
presented on the blockchain, which enhances trust
between the parties. For example, in the logistics sector,
smart contracts can automatically track the fulfillment
of transportation conditions. All key stages, such as
confirmation of loading, delivery, or payment, are
recorded on the blockchain, eliminating the need for
manual data entry and preventing fraud. This
significantly reduces coordination costs between
suppliers, carriers, and customers. In the financial
sector, smart contracts ensure the automatic execution
of loan agreements. In particular, if the borrower pays
interest on time, the smart contract immediately records
this and transfers the corresponding amount to the
lender, thus excluding intermediary costs (banking
institutions) and minimizing the risk of human errors.
The effectiveness of smart contracts is confirmed
by the successful experience of their use by large
companies. For example, the Danish shipping company
Maersk, in collaboration with IBM, uses smart contracts
through the TradeLens platform to manage container
shipping [8]. Meanwhile, the Australian energy
company Power Ledger uses smart contracts for buying
and selling solar energy from decentralized producers-
consumers [9].
As part of the Fourth Industrial Revolution, which
is accompanied by technological shifts in the field of
digitalization, data flows are the driving force behind the
transformation of the economic system. A particularly
important role in these changes is played by
mechanisms for collecting, processing, and exchanging
data. The use of outdated internet protocols to support
Industry 4.0 technologies, such as blockchain and 3D
printing, may significantly limit the economic impact of
their application. In the context of blockchain, for
example, this would lead to only a modest reduction in
transaction costs, as economic agents would be forced
to manually verify contract terms and update databases.
Meanwhile, in the case of 3D printing, the absence of
integrated communication channels between customers,
designers, and manufacturers would significantly
reduce the potential of this technology. However, the
Internet of Things (IoT) can solve this problem by
creating technological capabilities for automated data
exchange between devices and real-time data
processing. For example, IoT sensors installed on
vehicles can automatically send information about
successful product delivery to a blockchain system,
based on which a smart contract would automatically
transfer funds to the transport company's account.
Similarly, in the case of 3D printing, production
monitoring sensors can transmit information about the
need for additional parts to the 3D printer, which would
then automatically produce them.
It is also important to emphasize the role of the
Internet of Things as a self-sufficient, system-forming
technology. By enabling real-time communication
between producers and consumers of products, IoT
helps adapt the market to the actual needs of consumers.
This is achieved through the dynamic optimization of
business operations based on real-time information
about current product orders, consumer preferences,
inventory levels, and materials in warehouses, among
other factors. As a result, manufacturers reduce the risks
of overproduction, and consumers receive the desired
products, which is a hallmark of the "pull economy."
Conclusions. At the current stage of the Fourth
Industrial Revolution, particularly the transition to the
Industry 4.0 production model, Artificial Intelligence
technology is considered a breakthrough. On the one
hand, it radically reduces production costs, and on the
other hand, it enhances the effectiveness of
complementary technologies such as the Internet of
Things, 3D printing, and blockchain. Each of these
technologies, both individually and in combination,
contributes to changes in the established structural
elements of the economic system. 3D printing, in
combination with the Internet of Things infrastructure
and the computational capabilities of Artificial
Intelligence, simplifies the production of customized
products. This changes the structural element of the
economic system related to determining the product
range, i.e., addressing the question of "what to produce."
Moreover, 3D printing allows for the reduction of the
value creation chain, which in turn impacts the
production methods that define "how to produce." This
structural element of the system is also influenced by
blockchain technology, which provides opportunities
for reducing transaction costs in the regulatory
institutions governing relationships between economic
agents. Finally, the structural element of "for whom to
produce" is transformed under the influence of the
Internet of Things technology, which enables producers
to collect and analyze information about consumers,
ensuring that production is adapted to their individual
needs.
Literature
1. Schwab K. The Fourth Industrial Revolution. New-York: Penguin, 2017. 192 p.
2. Schwab K. Shaping the Future of the Fourth Industrial Revolution. New-York: Penguin, 2018. 351 p.
3. Moore G. Cramming more components onto integrated circuits. Electronics. 1965. Vol. 38. P. 33-35. DOI:
https://doi.org/10.1109/N-SSC.2006.4785860.
4. Perez C. Technological Revolutions and Financial Capital. The Dynamics of Bubbles and Golden Ages. Northampton: Edward
Elgar Publishing, 2002. 231 p. DOI: https://doi.org/10.4337/9781781005323.
5. Zuboff Sh. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York:
PublicAffairs, 2019. 704 p.
6. Тепскотт Д., Тепскотт А. Болкчейн революція. Як технологія, що лежить в основі біткойна та інших криптовалют,
змінює світ. Львів: Літопис, 2019. 487 с.
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25
Економічний вісник Донбасу № 4(78), 2024 ISSN 1817-3772
7. Your digital id. Republica of Estonia e-Residency. URL: https://www.e-resident.gov.ee.
8. TradeLens: Building a world of paperless trade. Tradelens. URL: https://www.tradelens.com.
9. Blockchain and decentralization. Powerledger. URL: https://powerledger.io/blockchain-technology.
References
1. Schwab, K. (2017). The Fourth Industrial Revolution. New-York, Penguin. 192 p.
2. Schwab. K. (2018). Shaping the Future of the Fourth Industrial Revolution. New-York, Penguin. 351 p.
3. Moore, G. (1965). Cramming more components onto integrated circuits. Electronics, Vol. 38, рр. 33-35. DOI:
https://doi.org/10.1109/N-SSC.2006.4785860.
4. Perez, C. (2002). Technological Revolutions and Financial Capital. The Dynamics of Bubbles and Golden Ages. Northampton,
Edward Elgar Publishing. 231 p. DOI: https://doi.org/10.4337/9781781005323.
5. Zuboff, Sh. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New
York, PublicAffairs. 704 p.
6. Tapscott. D., Tapscott. A. (2019). Blockchain revolution. How the technology behind Bitcoin and other cryptocurrencies is
changing the world. Lviv. Litopys. 487 p. [in Ukrainian].
7. Your digital id. Republica of Estonia e-Residency. Retrieved from https://www.e-resident.gov.ee.
8. TradeLens: Building a world of paperless trade. Tradelens. Retrieved from https://www.tradelens.com.
9. Blockchain and decentralization. Powerledger. Retrieved from https://powerledger.io/blockchain-technology.
Сердюк О. Технології Індустрії 4.0 як фактор розвитку економіки
В статті розглянуто потенціал технологій Індустрії 4.0 як фактора розвитку економічної системи. Проаналізовано
ключові технології Четвертої промислової революції, зокрема Штучний інтелект (ШІ), Інтернет речей (IoT), блокчейн та 3D-
друк, і їхній вплив на економічні процеси. Особливу увагу приділено ролі Штучного інтелекту, який є основним рушієм
трансформації виробничих процесів. Досліджено можливості автоматизації виробництва за допомогою ШІ, його здатність до
аналізу даних у реальному часі, управління ресурсами та оптимізації виробничих процесів. Встановлено, що впровадження
ШІ сприяє зниженню операційних витрат, покращенню якості продукції та ефективнішому використанню ресурсів.
Розглянуто Інтернет речей як технологію, що забезпечує інтеграцію виробничих процесів і комунікацію між пристроями в
режимі реального часу. Наголошено на його ролі у формуванні "розумних фабрик" та переході до моделі "витягаючої
економіки", яка дозволяє виробникам швидко адаптуватися до змін у споживчому попиті. Технологія блокчейн досліджується
в контексті зниження трансакційних витрат та забезпечення прозорості економічних відносин. Аналізуються перспективи
застосування смарт-контрактів у логістиці, фінансах та управлінні бізнес-процесами, а також потенційні загрози, пов’язані з
централізацією контролю над даними. 3D-друк розглядається як інструмент для оптимізації виробничих процесів та
персоналізації продукції.
Ключові слова: Індустрія 4.0, штучний інтелект, Інтернет речей, блокчейн, 3D-друк, економічна трансформація,
автоматизація виробництва.
Serdiuk O. Industry 4.0 Technologies as a Factor in Economic Development
The article explores the potential of Industry 4.0 technologies as a factor in the development of the economic system. It analyzes
the key technologies of the Fourth Industrial Revolution, namely Artificial Intelligence (AI), the Internet of Things (IoT), blockchain,
and 3D printing, and their impact on economic processes. Special attention is given to the role of Artificial Intelligence, which is the
main driver of the transformation of production processes. The possibilities of production automation through AI, its ability to analyze
real-time data, manage resources, and optimize production processes are examined. It is established that the implementation of AI
contributes to reducing operational costs, improving product quality, and more efficient resource utilization. The Internet of Things is
considered as a technology that enables the integration of production processes and communication between devices in real-time.
Emphasis is placed on its role in the formation of "smart factories" and the transition to a "pull economy" model, which allows
manufacturers to quickly adapt to changes in consumer demand. Blockchain technology is studied in the context of reducing transaction
costs and ensuring the transparency of economic relations. The prospects for the use of smart contracts in logistics, finance, and business
process management are analyzed, along with potential threats related to the centralization of control over data. 3D printing is
considered as a tool for optimizing production processes and personalizing products.
Keywords: Industry 4.0, artificial Intelligence, Internet of Things, blockchain, 3D printing, economic transformation, production
automation.
Received by the editors: 30.10.2024
Reviewed: 18.11.2024
|
| id | nasplib_isofts_kiev_ua-123456789-203370 |
| institution | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| issn | 1817-3772 |
| language | English |
| last_indexed | 2025-12-07T17:39:53Z |
| publishDate | 2024 |
| publisher | Інститут економіки промисловості НАН України |
| record_format | dspace |
| spelling | Serdiuk, O. 2025-05-23T09:29:01Z 2024 Industry 4.0 technologies as a factor in economic development / O. Serdiuk // Економічний вісник Донбасу. — 2024. — № 4 (78). — С. 19-25. — Бібліогр.: 9 назв. — англ. 1817-3772 https://nasplib.isofts.kiev.ua/handle/123456789/203370 338.2:004.8 https://doi.org/10.12958/1817-3772-2024-4(78)-19-25 The article explores the potential of Industry 4.0 technologies as a factor in the development of the economic system. It analyzes the key technologies of the Fourth Industrial Revolution, namely Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, and 3D printing, and their impact on economic processes. Special attention is given to the role of Artificial Intelligence, which is the main driver of the transformation of production processes. The possibilities of production automation through AI, its ability to analyze real-time data, manage resources, and optimize production processes are examined. It is established that the implementation of AI contributes to reducing operational costs, improving product quality, and more efficient resource utilization. The Internet of Things is considered as a technology that enables the integration of production processes and communication between devices in real-time. Emphasis is placed on its role in the formation of "smart factories" and the transition to a "pull economy" model, which allows manufacturers to quickly adapt to changes in consumer demand. Blockchain technology is studied in the context of reducing transaction costs and ensuring the transparency of economic relations. The prospects for the use of smart contracts in logistics, finance, and business process management are analyzed, along with potential threats related to the centralization of control over data. 3D printing is considered as a tool for optimizing production processes and personalizing products. В статті розглянуто потенціал технологій Індустрії 4.0 як фактора розвитку економічної системи. Проаналізовано ключові технології Четвертої промислової революції, зокрема Штучний інтелект (ШІ), Інтернет речей (IoT), блокчейн та 3D-друк, і їхній вплив на економічні процеси. Особливу увагу приділено ролі Штучного інтелекту, який є основним рушієм трансформації виробничих процесів. Досліджено можливості автоматизації виробництва за допомогою ШІ, його здатність до аналізу даних у реальному часі, управління ресурсами та оптимізації виробничих процесів. Встановлено, що впровадження ШІ сприяє зниженню операційних витрат, покращенню якості продукції та ефективнішому використанню ресурсів. Розглянуто Інтернет речей як технологію, що забезпечує інтеграцію виробничих процесів і комунікацію між пристроями в режимі реального часу. Наголошено на його ролі у формуванні "розумних фабрик" та переході до моделі "витягаючої економіки", яка дозволяє виробникам швидко адаптуватися до змін у споживчому попиті. Технологія блокчейн досліджується в контексті зниження трансакційних витрат та забезпечення прозорості економічних відносин. Аналізуються перспективи застосування смарт-контрактів у логістиці, фінансах та управлінні бізнес-процесами, а також потенційні загрози, пов’язані з централізацією контролю над даними. 3D-друк розглядається як інструмент для оптимізації виробничих процесів та персоналізації продукції. en Інститут економіки промисловості НАН України Економічний вісник Донбасу International and regional economics Industry 4.0 technologies as a factor in economic development Технології Індустрії 4.0 як фактор розвитку економіки Article published earlier |
| spellingShingle | Industry 4.0 technologies as a factor in economic development Serdiuk, O. International and regional economics |
| title | Industry 4.0 technologies as a factor in economic development |
| title_alt | Технології Індустрії 4.0 як фактор розвитку економіки |
| title_full | Industry 4.0 technologies as a factor in economic development |
| title_fullStr | Industry 4.0 technologies as a factor in economic development |
| title_full_unstemmed | Industry 4.0 technologies as a factor in economic development |
| title_short | Industry 4.0 technologies as a factor in economic development |
| title_sort | industry 4.0 technologies as a factor in economic development |
| topic | International and regional economics |
| topic_facet | International and regional economics |
| url | https://nasplib.isofts.kiev.ua/handle/123456789/203370 |
| work_keys_str_mv | AT serdiuko industry40technologiesasafactorineconomicdevelopment AT serdiuko tehnologíííndustríí40âkfaktorrozvitkuekonomíki |