Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems
Background. Logistical gaps and territorial deformations of production capacities create unprecedented challenges for the dairy industry. This requires modernising capital investment management by transitioning to strategic investment in intelligent control systems, revising financial mechanisms, an...
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2026
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| author | Furman, Irina Revkova, Anna Biletska, Nataliia Svynous, Nadiia |
| author_facet | Furman, Irina Revkova, Anna Biletska, Nataliia Svynous, Nadiia |
| author_institution_txt_mv | [
{
"author": "Irina Furman",
"institution": "Vinnytsia National Agrarian University, Vinnytsia, Ukraine"
},
{
"author": "Anna Revkova",
"institution": "Vinnytsia National Agrarian University, Vinnytsia, Ukraine"
},
{
"author": "Nataliia Biletska",
"institution": "Interregional Academy of Personnel Management, Kyiv, Ukraine "
},
{
"author": "Nadiia Svynous",
"institution": "University of Economics and Entrepreneurship, Khmelnytskyi, Ukraine"
}
] |
| author_sort | Furman, Irina |
| baseUrl_str | https://ees-journal.com/index.php/journal/oai |
| collection | OJS |
| datestamp_date | 2026-06-30T15:36:44Z |
| description | Background. Logistical gaps and territorial deformations of production capacities create unprecedented challenges for the dairy industry. This requires modernising capital investment management by transitioning to strategic investment in intelligent control systems, revising financial mechanisms, and integrating environmental sustainability into the “from farm to fork” concept to ensure enterprise viability.
Purpose. The purpose is to substantiate the development of a model for capital investment management by integrating end-to-end digital technologies into the “farm-to-fork” value chain, combining physical asset management (CAPEX) with the implementation of biogas (Bio-CNG) infrastructure.
Findings. Analysis of the dynamics of gross milk production and investment activity in Ukraine in 2020–2024 revealed a deep structural transformation of the dairy market, characterised by a transition to intensive business models and the redistribution of production capacities toward the western and central regions. The strategic architecture of investment support enabled the formation of a holistic system of digital control over capital investments, ensuring the transition from spontaneous capacity renewal to strategic management of financial resources and increased enterprise competitiveness in the global dairy market. The use of AI-based predictive maintenance and digital twins optimises CAPEX and reduces OPEX by integrating renewable energy (Bio-CNG) into the logistics chain. The proposed model demonstrates how digital transparency creates premium value for products through eco-labelling and blockchain verification. The implementation of the Value-Chain Digital Control Model ensured a 75% increase in net profit, an increase in return on investment from 20% to 35% (by 15 percentage points), and a 44% reduction in the payback period (from 5 to 2.8 years).
Implication. The dairy sector demonstrates adaptive resilience, with a trend toward producing high-value-added products for export. The developed digital architecture “from farm to fork” (Blockchain and Internet of Things) provides end-to-end quality control and protection of intellectual capital. The integration of bio-CNG infrastructure is a critical driver of energy independence and reduced logistics costs. Digital modernisation, combined with social and environmental responsibility, is identified as a priority mechanism for ensuring the competitiveness of Ukrainian dairy enterprises in the EU markets. |
| doi_str_mv | 10.61954/2616-7107/2026.10.2-3 |
| first_indexed | 2026-07-01T01:00:35Z |
| format | Article |
| fulltext |
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
39
Research Article
UDC 662.756:620.92
JEL: Q16, Q18, Q42, O13, O44
VALUE-CHAIN DIGITAL CONTROL MODEL OF
CAPITAL INVESTMENT OPTIMISATION AND
QUALITY ASSURANCE IN FARM-TO-FORK
SYSTEMS
Irina Furman *
Vinnytsia National Agrarian University,
Vinnytsia, Ukraine
ORCID iD: 0000-0002-9923-555X
Anna Revkova
Vinnytsia National Agrarian University,
Vinnytsia, Ukraine
ORCID iD: 0000-0003-2622-5681
Nataliia Biletska
Interregional Academy of Personnel
Management,
Kyiv, Ukraine
ORCID iD: 0000-0001-6922-3614
Nadiia Svynous
University of Economics and
Entrepreneurship,
Khmelnytskyi, Ukraine
ORCID iD: 0000-0003-3640-0519
*Corresponding author:
E-mail: irina_furman@ukr.net
Background. Logistical gaps and territorial deformations
of production capacities create unprecedented challenges for the
dairy industry. This requires modernising capital investment
management by transitioning to strategic investment in intelligent
control systems, revising financial mechanisms, and integrating
environmental sustainability into the “from farm to fork” concept
to ensure enterprise viability.
Purpose. The purpose is to substantiate the development
of a model for capital investment management by integrating
end-to-end digital technologies into the “farm-to-fork” value
chain, combining physical asset management (CAPEX) with the
implementation of biogas (Bio-CNG) infrastructure.
Findings. Analysis of the dynamics of gross milk
production and investment activity in Ukraine in 2020–2024
revealed a deep structural transformation of the dairy market,
characterised by a transition to intensive business models and the
redistribution of production capacities toward the western and
central regions. The strategic architecture of investment support
enabled the formation of a holistic system of digital control over
capital investments, ensuring the transition from spontaneous
capacity renewal to strategic management of financial resources
and increased enterprise competitiveness in the global dairy
market. The use of AI-based predictive maintenance and digital
twins optimises CAPEX and reduces OPEX by integrating
renewable energy (Bio-CNG) into the logistics chain. The
proposed model demonstrates how digital transparency creates
premium value for products through eco-labelling and blockchain
verification. The implementation of the Value-Chain Digital
Control Model ensured a 75% increase in net profit, an increase
in return on investment from 20% to 35% (by 15 percentage
points), and a 44% reduction in the payback period (from 5 to 2.8
years).
Implication. The dairy sector demonstrates adaptive
resilience, with a trend toward producing high-value-added
products for export. The developed digital architecture “from
farm to fork” (Blockchain and Internet of Things) provides end-
to-end quality control and protection of intellectual capital. The
integration of bio-CNG infrastructure is a critical driver of
energy independence and reduced logistics costs. Digital
modernisation, combined with social and environmental
responsibility, is identified as a priority mechanism for ensuring
the competitiveness of Ukrainian dairy enterprises in the EU
markets.
Keywords: Biogas, Blockchain, Dairy Industry,
Investment Management, Supply Chain Management.
Received: 27/02/2026
Revised: 31/05/2026
Accepted: 08/06/2026
Published: 30/06/2026
DOI: 10.61954/2616-7107/2026.10.2-3
© Economics Ecology Socium, 2026
CC BY-NC 4.0 license
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
40
1. Introduction.
Against the backdrop of wartime and post-
war conditions in Ukraine, the dairy industry
faces unprecedented challenges, including
political turbulence, disruptions to logistics
networks, and the fragmentation of production
capacities across territories. Modernisation of
the mechanism for managing capital
investments at dairy processing enterprises is
impossible without the widespread adoption of
digitalisation tools that enable moving from
spontaneous renewal of fixed assets to strategic
investment in intelligent control systems. The
organisational reform of agribusiness is an
important basis for such transformations, as it
lays the institutional foundation for adapting
economic structures to changing market
conditions.
Soteriades et al. (2018) claim that
implementing innovative methods for feed and
manure management significantly reduces the
ecological footprint of dairy farms without
compromising economic efficiency.
The effectiveness of investment processes
in modern conditions directly depends on the
transparency of the information environment; in
particular, high-quality financial reporting is a
critical factor for the objective assessment of
enterprise performance and capital attraction
(Pravdiuk et al., 2021).
The industry’s digital transformation
requires a reassessment of traditional
mechanisms for resource and financial
management. In particular, the use of supply
chain financing tools and modern inventory
management systems is critical for optimising
capital investments, especially for products with
a limited shelf life (Marchi et al., 2024).
It is the synergy between environmental
sustainability and digital financial technologies
that underpins an effective architecture for
managing capital investments in dairy
processing enterprises within the Farm-to-Fork
Strategy framework. At the same time, the
industry’s strategic development should focus
on sustainable marketing, enabling Ukrainian
agricultural enterprises not only to adapt to
internal challenges but also to compete
successfully in global food markets (Belkin et
al., 2025).
Despite significant theoretical
developments, the practical implementation of
end-to-end digital control systems in Ukrainian
realities remains insufficiently explored. The
identified need to develop a comprehensive
model of digital supply chain management
shapes further research on the practical
implementation of agri-food chains and
addresses the lack of an applied model that
simultaneously optimises capital investments
(CAPEX) under limited resources and ensures
end-to-end quality control of food products.
The purpose of the study is to substantiate
the theoretical and methodological principles
and develop applied tools for forming a model
of capital investment management of dairy
processing enterprises, based on the integration
of end-to-end digital technologies (blockchain,
IoT, AI) into the farm-to-fork value chain to
ensure investment sustainability, environmental
safety, and energy independence of the industry
under martial law. To achieve the research aim,
the following research questions (RQs) were
identified:
RQ1. To assess the dynamics of gross
milk production, investment activity, and
foreign trade balance of Ukraine for 2020–2024,
taking into account the impact of military
operations.
RQ2. To investigate the territorial
configuration of the dairy industry and identify
the main centres of added value formation and
investment leadership.
RQ3. To develop an author’s model of an
end-to-end digital control system that integrates
blockchain technologies, the industrial IoT, and
artificial intelligence to ensure the quality and
protection of capital investments.
RQ4. To substantiate the mechanism of
combining physical asset management
(CAPEX) with the implementation of biogas
infrastructure and adaptive management
methods to increase the sustainability of
enterprises.
Therefore, the development and
implementation of an end-to-end digital control
system is a strategic tool for transforming
Ukrainian dairy processing enterprises into
modern and highly efficient agribusiness
facilities.
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
41
2. Literature Review.
2.1. Farm-to-Fork Concept.
The current state of the global and
domestic food industry is characterised by deep
transformation, driven by the need to balance
economic efficiency, environmental
sustainability, and consumer demands. The key
concept uniting these aspects is the “farm-to-
fork” model, which aims to optimise supply
chains and increase the transparency of
production processes.
The genesis of the “farm-to-fork” concept
is closely related to the transformation of
consumer values and the search for alternatives
to globalised food systems. A fundamental
contribution to understanding the importance of
local connections was made by Waters (2007)
demonstrated the dependence of final product
quality and agricultural sector sustainability on
ethical attitudes towards the land and direct
support for small producers. This approach
transformed the gastronomic niche into a
systemic movement for transparency in the
origin of food products.
This initiative has evolved into a global
sustainability initiative. Pollan (2006) argues
that the gap between the “farm and fork” in the
modern industrial system has resulted in a loss
of control over energy costs and nutritional
quality. Reducing the supply chain is considered
the only way to restore food sovereignty and
minimise climate impacts. This concept has
become an official strategy for developing agro-
industrial complexes in developed countries.
According to the European Commission (2020),
the transition to a sustainable food system
requires not only changes in consumption
culture but also a digital transformation of
production processes. This creates the
prerequisites for a new architecture of capital
investment management, where information
about each stage of a product’s movement, from
primary raw materials to final sale.
Kelly et al. (2025) stated that
understanding the aspects of milk
transformation at each stage of the chain, from
lactation biology to complex processing
technologies, is critical to ensuring product
integrity and compliance with modern quality
standards.
It should also be noted that food safety
remains a global problem, as hazardous
substances can occur throughout the food
supply chain, from farm to fork (Tian et al.,
2025).
In contrast to the residual approach,
Serpeninova et al. (2024) identified an approach
that considers social responsibility as
compensation after profit is made. An integrated
approach involves incorporating economic,
social, and environmental factors (particularly
quality control along the “farm-to-fork” chain)
directly into decision-making. This creates
conditions for ensuring economic development
by considering the environmental and social
consequences of an enterprise’s activities.
Furthermore, Koval et al. (2025) showed
that dairy enterprises face a wide range of
challenges, including political and economic
turbulence, disruptions in logistics networks,
and changes in consumer sentiment.
The modern “farm-to-fork” paradigm
requires a comprehensive quality assurance
approach that begins at the genetic potential and
feeding stages of the animals. Mukherjee et al.
(2025) argue that the transition from
conventional breeding systems to sustainable
production in the genomic era is the foundation
of global food security, as it enables the
programming of product quality characteristics
at the breeding level.
Precision nutritional approaches
accompany this process. In particular, Kazemi
and Valizadeh (2025) as well as Mukherjee et
al. (2025) emphasised that the implementation
of innovative feeding strategies is a key lever
for increasing the biological value and safety of
animal-based food products that meet the
growing consumer demand for functional foods.
An important aspect of the dairy market
evolution is the differentiation of products based
on health benefits. Manuelian et al. (2025)
found that consumer acceptance of innovative
products, such as type A2 milk, creates new
niches and potential markets, requiring
producers to be transparent about the production
and consumption practices. This confirms that
modern quality is not only about meeting
standards but also about the ability to meet
specific consumer needs within the farm-to-fork
chain.
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
42
Digitalisation unites these processes
technologically. According to a systematic
review (Serrano-Torres et al., 2025),
transforming dairy supply chains through AI
enables end-to-end real-time quality control.
This creates a solid foundation for a capital
investment management architecture that
leverages AI to minimise risks, optimise
logistics, and guarantee product authenticity,
critical to ensuring the resilience of dairy
processing enterprises in crisis conditions.
The “farm-to-fork” concept and the
corresponding investment architecture are
particularly relevant to overcoming the
destructive consequences of military operations
on Ukraine’s agricultural sector.
Nitsenko et al. (2025) argue that the
current state of domestic agribusiness requires
the immediate revitalisation of logistics and
handling operations activities and the strategic
relocation of logistics processes. In the context
of territorial deformations and the blocking of
traditional routes, effective risk management
and flexible restructuring of logistics chains are
critical for maintaining the viability of the
industry’s export and domestic potential. This
directly correlates with the need to develop
digital models of capital investment
management that enable dairy processing
enterprises to quickly adapt their value chains
to the changed conditions resulting from the
dislocation of production facilities and new
logistical challenges.
The identified shortcomings of the
developed sources indicate the fragmentation
of investment models that do not offer clear
capital management algorithms in conditions of
limited resources and high risks of asset
destruction. Thus, there is an objective need to
develop an integrated investment management
model that combines environmental “farm-to-
fork” standards with flexible anti-crisis
marketing methods and digital control.
2.2. Digital Management of Capital
Investments.
In the context of digitalisation, the
technological architecture for managing dairy
investments is shifting from equipment renewal
to the creation of intelligent systems.
The synergy of artificial intelligence, IoT,
and Blockchain provides end-to-end quality
control from “farm-to-fork”, optimising
resources and strengthening the enterprise’s
intellectual capital. Military challenges require
implementing flexible Agile methods to rapidly
relocate logistics and adapt investments to the
risks of asset destruction. Thus, digital
architecture becomes the foundation for energy
independence and the industry’s survival in
turbulent conditions.
Czeglédi (2025) eliminated the gap
between the cultivation and consumption of
agricultural products. The corresponding model
promotes a direct connection between producers
and end consumers. Although a “farm-to-fork”
model is the shortest, this streamlined approach
minimises logistical and administrative
complexities, reducing the distance and time
between harvest and consumption to a
minimum.
Kelly et al. (2025) argue that, despite the
very long history of dairy products and their
high level of consumption in the world today,
the future of the dairy industry is now perhaps
under greater threat than at any time in history,
with the emergence of concerns about the
health, ethical and environmental impacts of
dairy production, as well as the rise of veganism
and the associated desire to find alternatives to
dairy products.
According to Subbotina-Dubinski and
Carbon (2025), the main thematic clusters
related to changes in the food industry in
general (sustainable food practices) and dairy in
particular (empirical dimensions of food).
Yin (2025) and Mosiuk et al. (2025)
argued that cognitive and emotional reactions of
customers mediate the influence of restaurant
incentives, especially environmental practices,
on pro-environmental behaviour and
behavioural intentions of consumers during
dining, thereby influencing the effective
development of responsible strategies in
environmentally conscious food establishments.
This shift towards responsible consumption and
reputation-based value creation has a direct
impact on capital investment management in the
agri-food sector, particularly in dairy
processing.
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
43
Lohosha et al. (2024) argue that efforts
should be made in Ukraine to develop a
separate, original regulatory concept based on a
contractual approach (as an internal mechanism
for coordinating the actions of economic agents
in the market). State regulation (as an external
instrument for shaping regulatory rules
governing the behaviour of market
participants/relationships) to achieve an
acceptable market state.
Chikov and Titov (2025) show that
modernising the mechanism for capital
investment management at dairy processing
enterprises is impossible without widespread
digitalisation. It allows moving from the
spontaneous renewal of fixed assets to strategic
investment in intelligent control systems, which
becomes the foundation for increasing the
industry’s competitiveness.
It is worth noting that, according to
Popovych et al. (2023), the economic
efficiency of digitalisation in the dairy sector
is manifested in increased labour productivity
and reduced costs through resource
optimisation. Stavska et al. (2022) indicated
that agile development helps product groups
deliver software that meets customers’
growing needs.
Simultaneously, the successful
implementation of an end-to-end digital control
system in dairy processing enterprises depends
not only on technical equipment but also on the
intellectual basis of the organisation. Pidvalna
et al. (2022) argue that developing an
innovative strategy should be based on
building intellectual capital, which is
imperative for ensuring the sustainability of
enterprises in the context of digitalisation.
Ensuring the sustainable development of
the agri-food sector, particularly the dairy
industry, is only possible using an integrated
approach. While Serpeninova et al. (2024) and
Koval et al. (2025) emphasise the importance
of corporate social responsibility and
sustainable management, Chikov and Titov
(2025), Popovych et al. (2023), and Stavska et
al. (2022) indicate that the technical foundation
of sustainability is digitalisation, the
implementation of IoT tools, and agile
management.
However, despite significant research on
the “farm-to-fork” concept and the importance
of intellectual capital (Pidvalna et al., 2022),
the issue of the practical implementation of
end-to-end digital control systems in the
context of the war- and post-war economy of
Ukraine remains insufficiently covered. In
particular, the mechanism of combining
contractual market regulation (Lohosha et al.,
2024) with technological innovations to
address logistical gaps and personnel shortages
(Mosiiuk, 2026) requires further study.
Thus, the need to develop a
comprehensive model of digital supply chain
management that integrates intellectual
property, social responsibility, and high food
safety standards has been identified, which will
determine the direction of this research.
3. Methodology.
The research methodology is based on a
complex combination of general scientific and
specialised methods that enable a deep analysis
of the investment architecture of the dairy
industry under martial law and in the context of
digital transformation.
The research process begins with a
retrospective analysis of the dynamics of milk
production and the cow population for 2020–
2024, which enables identification of critical
points of decline in raw material volumes and
deformation of the industry's territorial
structure. At the next stage, the method of
statistical and economic screening was applied
to assess capital investments and export-import
operations, thereby enabling the determination
of the level of financial stability of dairy
processing enterprises.
An important place in the work is
occupied by the method of economic and
mathematical modelling, which was used to
design a digital control system for the "farm-
to-fork" strategy, integrating blockchain,
artificial intelligence, and IoT tools to
minimise operating costs. In addition, the study
substantiates the implementation of energy-
efficient infrastructure based on Bio-CNG, as
demonstrated by return on investment (ROI)
and capital expenditure optimisation (CAPEX)
indicators.
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
44
Verification of the results is carried out
by comparing theoretical models with actual
data from the State Statistics Service of
Ukraine (2025) and customs reporting, which
confirms the practical value of the proposed
solutions for increasing the investment
attractiveness of the agricultural sector. The
use of a systemic approach enables the
development of a holistic vision of the dairy
business as a vertically integrated structure
capable of adapting to global challenges and
meeting European quality standards. The
model is based on the calculation of the
effectiveness of cost optimisation:
𝑅𝑂𝐼 ∗ 100% (1)
To assess the impact of digital control on
operating expenditures (OPEX), the functional
dependence is used:
∆𝑂𝑃𝐸𝑋 𝐶 𝐶 𝐸 𝐸 (2)
where,
Clog – costs on traditional logistics;
Cmaint – costs on reactive equipment
maintenance;
Ebio – savings from the use of BioCNG;
Eai – savings from the implementation of
AI-predictive maintenance.
The methodology for developing the
model of an end-to-end digital control system
involves integrating technological tools into a
single architecture to optimise capital
investments across the value chain. The
methodology is based on an algorithm for
identifying key “farm-to-fork” links and the
selection of appropriate digital technologies,
such as blockchain to ensure the safety of raw
materials, industrial IoT for predictive
maintenance of equipment, and artificial
intelligence for modelling energy-efficient
solutions.
The model is developed by combining
CAPEX with intellectual property protection
and the implementation of adaptive
management methods (Agile management). The
final stage of building the model involves
systematising economic components, where the
use of digital twins and quality verification
systems maximises net profit, ensures energy
independence through Bio-CNG infrastructure,
and creates premium product value in global
markets.
The proposed investment architecture for
the dairy industry is based on the concepts of
vertical integration and the digitalisation of the
full value-creation cycle, in line with the “Farm-
to-Fork” Strategy (Fig. 1).
Fig. 1. Strategic Framework for Sustainable Dairy Investment under Green and Digital
Transition.
Level 1:
Technological Foundation
Level 2:
Operating management
Level 3:
Information Transparency
Level 4:
Economic result
Capital investments in the
modernisation of investment
farms and the construction of
biogas plants
Development of BioCNG, logistics,
and implementation of AI models at
dairy plants
Blockchain verification (full
traceability of products (“farm-to-
fork”) and building digital trust
ROI growth
Waste processing in biogas
plants, management
modernisation
Modernisation of production and
logistics processes
QR coding on the final product
with the possibility of
familiarising yourself with the
full production cycle
Eco-labelling
Formation of premium
value
R
einvestm
ent based on
the principles of circular
econom
y
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
45
The model is based on a systematic
combination of a technological foundation,
including investments in IIoT sensors and
biogas infrastructure for the production of Bio-
CNG fuel, with a digital level of operational
management based on artificial intelligence.
The industry transformation process is
implemented through a blockchain-based
verification mechanism at each stage of product
movement, providing absolute transparency and
traceability for the end consumer.
Economic efficiency is achieved through
radical optimisation of operating costs and the
creation of premium value for environmentally
labelled products, which directly correlates with
the growth of investment profitability indicators
and the enterprise’s overall investment
sustainability in the face of global challenges.
The model’s closed cycle involves the constant
reinvestment of profits into the development of
innovative infrastructure, creating a sustainable
circular ecosystem for the dairy business. The
analysis does not cover temporarily occupied
territories or combat zones.
The BioCNG infrastructure model is
considered a tool for optimising logistics,
specifically for large and medium-sized milk
plants with an intensive business model.
4. Results.
4.1. Analysis of the State of the Dairy
Processing Industry in Ukraine.
The analysis of milk production volumes
and industry activities indicates a deep
structural transformation of Ukraine’s dairy
market, characterised by a transition to intensive
business models amid a gradual reduction in the
total number of cows from 2.54 million in 2013
to a projected 1.15 million in 2025.
Despite the overall decrease in the volume
of milk supplied for processing, there is a
qualitative increase in the role of the industrial
sector, where the volume of raw material
supplies from agricultural enterprises increased
to 2.88 million tons in 2024, which confirms the
dominance of professional farms in ensuring
food stability (Fig. 2).
Fig. 2. Dynamics of Cow Population and Milk Supply for Processing in Ukraine.
* - data are updated without temporarily occupied territories.
Source: based on data Association of Milk Producers (2025).
Despite martial law and the loss of part of
the production capacity, in 2024, the agricultural
sector of Ukraine recorded a gross milk
production volume of 7,246.4 thousand tons,
which indicates a deep transformation of the
industry and a change in its territorial
configuration (Fig. 3). The current state of dairy
cattle breeding is characterised by pronounced
regional concentration, where the leading
positions are occupied by Poltava, Vinnytsia, and
Khmelnytsia regions, which together provide a
significant share of national raw material
production due to the preservation of livestock
and high productivity of the industrial herd.
2.43 2.21 2.10 2.02 1.92 1.78 1.67 1.55 1.34 1.29 1.22 1.15
0.58 0.57 0.53 0.5 0.48 0.47 0.47 0.44 0.42 0.42 0.38 0.39 0.38
4.66 4.66
4.31 4.18 4.3 4.17
3.8
3.51
3.24
2.44
2.86
3.12 3.23
2.27 2.42 2.41 2.51 2.65 2.72 2.61 2.56 2.48
2.18
2.55
2.88 2.97
0.00
1.00
2.00
3.00
4.00
5.00
2013 2014 2015* 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024* 2025*
Number of cows (total), million heads Number of cows at agricultural enterprises, million heads
Milk supplied for processing (total), million tons Milk supplied by agricultural enterprises, million tons
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Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
48
Table 2. Volume of Imports and Exports of Dairy Products (thousands USD), 2020–2024.
2020
Product (UKTZED Code)
Import Export
Cost Share Net weight, t Cost Share Net weight, t
Milk and cream, not
condensed
11,624 0.02% 12,969 12,006 0.02% 18,642
Milk and cream, condensed 14,005 0.03% 6,144 55,529 0.11% 27,417
Buttermilk, fermented or
soured milk, and cream
14,029 0.03% 9,921 8,974 0.02% 5,694
Whey 6,920 0.01% 5,062 22,304 0.05% 26,904
Butter 40,580 0.07% 10,012 48,733 0.10% 11,229
Cheese 210,487 0.39% 46,767 24,414 0.05% 6,358
2021
Product (UKTZED Code)
Import Export
Cost Share Net weight, t Cost Share Net weight, t
Milk and cream, not
condensed
13,377 0.02% 14,369 10,372 0.02% 14,922
Milk and cream, condensed 21,204 0.03% 7,799 57,366 0.08% 22,426
Buttermilk, fermented or
soured milk, and cream
20,008 0.03% 14,005 8,649 0.01% 5,504
Whey 12,335 0.02% 9,628 22,821 0.03% 22,218
Butter 45,529 0.06% 9,148 52,308 0.08% 10,858
Cheese 260,329 0.36% 55,193 26,692 0.04% 6,924
2022
Product (UKTZED Code)
Import Export
Cost Share Net weight, t Cost Share Net weight, t
Milk and cream, not
condensed
8,594 0.01% 9,386 16,387 0.04% 29,350
Milk and cream, condensed 4,027 0.01% 1,214 89,983 0.20% 26,696
Buttermilk, fermented or
soured milk, and cream
14,938 0.03% 9,456 4,668 0.01% 3,055
Whey 6,904 0.01% 4,917 15,765 0.04% 15,269
Butter 7,910 0.01% 1,128 81,742 0.19% 14,104
Cheese 182,159 0.31% 33,818 42,278 0.10% 8,989
2023
Product (UKTZED Code)
Import Export
Cost Share Net weight, t Cost Share Net weight, t
Milk and cream, not
condensed
6,069 0.01% 5,126 16,572 0.05% 28,315
Milk and cream, condensed 4,738 0.01% 1,263 68,670 0.19% 27,676
Buttermilk, fermented or
soured milk, and cream
17,376 0.03% 8,670 4,172 0.01% 3,353
Whey 12,474 0.02% 6,887 10,854 0.03% 16,181
Butter 16,633 0.03% 2,657 41,770 0.12% 7,790
Cheese 200,774 0.32% 33,685 39,962 0.11% 8,879
2024
Product (UKTZED Code)
Import Export
Cost Share Net weight, t Cost Share Net weight, t
Milk and cream, not
condensed
4,048 0.01% 2,021 17,620 0.04% 26,601
Milk and cream, condensed 5,321 0.01% 1,520 74,284 0.18% 29,487
Buttermilk, fermented or
soured milk, and cream
16,820 0.02% 8,189 5,917 0.01% 4,375
Whey 10,813 0.02% 6,088 13,377 0.03% 18,685
Butter 18,577 0.03% 2,576 48,897 0.12% 7,178
Cheese 227,088 0.32% 38,284 54,208 0.13% 12,428
Source: based on State Customs Service of Ukraine (2025).
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Cheese remains the most significant
import item throughout the entire period, and its
value reaches USD 227.1 million in 2024, an
increase of 8,483 tons from 2020.
Simultaneously, the export sector experienced
rapid growth in condensed milk and butter, with
sales peaking in 2022, when butter exports
almost doubled from the previous year to USD
81.74 million. Despite the general trend of
increasing exports of whole milk and cream by
7,959 tons, deliveries of buttermilk and whey
abroad showed a negative deviation, indicating
a reorientation of domestic processing.
As of 2024, domestic producers
significantly strengthened their positions in
foreign cheese markets, increasing exports by
6.1 thousand tons, compared to the base period.
Together with the dominance of condensed milk
in the export structure, this underscores the
industry’s strategic development of high-value
products. The reduction in the imports of butter
and non-condensed dairy products in 2022–
2024, compared to 2021, indicates successful
import substitution and the dairy sector’s
adaptation to crisis operating conditions.
The identified negative deviation in the
export of certain categories, along with the
preservation of a high share of cheese imports,
underscores the need for new competitiveness
tools that focus on the digital management of
the value chain.
The analysis of the foreign trade balance
and regional investment structure indicates the
presence of an institutional trap. Despite
increased industrial sector efficiency, the
industry remains vulnerable to fluctuations in
energy carrier prices and the strict requirements
of European safety standards. This determines
the objective need to transition from fragmented
automation to a comprehensive digital
architecture that integrates physical asset
management (CAPEX) with the protection of
the enterprise’s intellectual capital.
4.2. Digital Transformation of the
Farm-to-Fork Value Chain for
European Market Integration.
It is worth noting that the transformation
of the Ukrainian dairy sector under war
conditions involves not only relocating
production facilities but also deep digital
modernisation, which is key to preserving
capital and entering premium European
markets. Ensuring the above-mentioned
sustainability of export potential and CAPEX
efficiency requires a transition to fundamentally
new technological foundations, which are
systematised in Table 3.
Table 3. Digital Transformation and Investments Optimisation in the Farm-to-Fork Value Chain.
Strategic Task
Supply Chain
Stage
Key Digital
Technologies
Impact on CAPEX, ROI, and
Quality Assurance
Blockchain-based traceability for
digital raw material management,
ensuring product origin, quality,
and safety.
Farm →
Processing
Blockchain, IoT
Sensors
Improved traceability, enhanced
quality assurance, reduced food
safety risks, and lower production
losses.
Predictive maintenance to
safeguard investments in critical
processing equipment.
Processing
IIoT, AI-based
Predictive
Maintenance
Cost and downtime reduction,
improved reliability, and CAPEX
preservation.
Strategic investment in biogas
production and Bio-CNG
infrastructure to reduce logistics-
related operating costs and
strengthen energy resilience.
Recycling /
Biogas
Production
Digital Twins,
AI-Based
Modelling
Improved justification of CAPEX
allocated to biogas facilities through
long-term OPEX savings, waste
valorisation, and enhanced energy
independence.
End-to-end monitoring of green
logistics through cold-chain
control and optimisation of Bio-
CNG-powered transport routes.
Logistics
IoT Sensors,
GPS/Telematics,
AI Optimisation
Improved product quality and safety
during transportation. Efficient
utilisation of logistics assets and
reduced transportation costs.
Maximising return on investment
through digital transparency,
sustainable logistics, and
consumer-oriented value creation.
Consumer /
Market
Blockchain,
Digital
Marketing
Integration
Faster ROI driven by consumer trust,
brand loyalty, and willingness to pay
a premium for certified quality and
sustainability.
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As a result of the research, we conducted
a comprehensive analysis of the implementation
of innovative technologies at each stage of the
agri-food cycle.
It reveals the mechanisms for integrating
blockchain, the Industrial Internet of Things
(IIoT), and artificial intelligence to ensure end-
to-end transparency of raw material flows,
predictive maintenance of expensive equipment,
and justification of capital investments in
renewable energy, in particular, Bio-CNG
infrastructure.
The production of biogas from dairy
processing waste is particularly relevant given
rising energy prices. In general, the application
of this chain demonstrates the transition to a
sustainable, high-tech agribusiness model,
where environmental responsibility and digital
verification become key drivers of higher
margins and premium product value in the
market. The comprehensive architecture of the
digital management model for the farm-to-fork
chain, presented in Table 4, reveals a
multifaceted approach to transforming dairy
processing enterprises through the synergy of
technological transparency, capital
management, and strengthening the
organisation's intellectual base. This structure
demonstrates how integrating blockchain,
industrial IoT, and AI modelling tools not only
enables end-to-end control from farm to
consumer but also provides a reliable
foundation for enterprise sustainability amid
global digital transformations. Particular
attention in the architectonics is paid to the
combination of social and environmental
responsibility with adaptive management
methods, which, through the implementation of
Agile management and "green" infrastructure,
helps overcome logistical gaps and increase
business margins by creating a premium value
for the end consumer.
Table 4. Digital Management Architecture for the Farm-to-Fork Value Chain in Dairy
Processing Enterprises.
Component of the
Model
Key Tools and
Technologies
Object of Integration
and Influence
Economic and Social Impact
Technological
Transparency and
Security
Blockchain, IoT
sensors, AI modelling
End-to-end control from
farm to end consumer
Minimising food safety risks
and ensuring product quality
Capital and
Investment
Management
Predictive maintenance
(IIoT), digital twins
Protection of expensive
equipment and assets
(CAPEX)
Reducing unforeseen costs,
maximising ROI, and
achieving energy
independence
Intellectual Capital
Development
Protection of
intellectual property,
development of
intellectual capital
Innovative development
strategy and
commercialisation of ideas
Formation of economic
sustainability of the enterprise
in the context of digital
transformations
Socio-
Environmental
Responsibility
Sustainable food
practices, Bio-CNG
infrastructure, ESG
reporting
Corporate social
responsibility and
environmental verification
Increasing marginality
through the formation of
premium value for the
conscious consumer
Adaptive
Management
Agile management
(Management 3.0), anti-
crisis marketing
Flexibility of production
and logistics chains in
wartime
Overcoming logistical gaps
and personnel shortages
The systematisation of economic
components of the model, presented in Table 5,
reveals a specific mechanism for converting
digital tools into effective financial indicators at
each stage of the enterprise’s capital
reproduction cycle.
It displays the strategic relationship
between the use of digital twins to justify
investments (CAPEX) in modernisation and
energy independence, and the final optimisation
of the capital investment structure (Soteriades et
al., 2018).
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At the production and logistics stages,
the use of intelligent monitoring systems and
blockchain provides effective protection of
fixed assets and a significant reduction in
operating expenses (OPEX), which ultimately
allows for maximising net profit and ROI
through the use of digital quality verification as
a key factor in the formation of a premium price
in the market. Thus, the developed model
confirms that implementing an end-to-end
digital verification system and complying with
social and environmental responsibility
standards are key tools for ensuring the
sustainability of the agri-food sector.
This establishes the prerequisites for
increasing the marginality of domestic products
and their successful integration into the
European economic space, based on
transparency, quality, and high technological
competitiveness.
The justification of the proposed model
is based on the integration of digital
management systems with bioenergy
infrastructure, which allows maximising the
efficiency of capital investments, which in 2025
were recorded at the level of USD 164.8 million
for the entire food industry and USD 24.1
million directly for the Vinnytsia region using
the example of an advanced dairy processing
enterprise, Lityn Dairy Plant LLC (Litynskyi
Molochnyi Zavod LLC).
The implementation of digital control
using the Value-Chain Digital Control algorithm
transforms the traditional approach to CAPEX
management, reorienting resources toward the
creation of intelligent monitoring systems and
biomethane infrastructure, thereby increasing
net profit from a conventional USD 400 to 700
thousand per year for an average facility in the
industry. The main economic effect is achieved
through a radical reduction in operating costs
due to the complete replacement of fossil fuels
with its own Bio-CNG, which frees up about
USD150 thousand annually, as well as through
the use of artificial intelligence for predictive
maintenance of equipment, which saves
additional USD 50 thousand per year on service
costs.
Table 5. Economic Components and Financial Effects of the Digital Farm-to-Fork
Management Model
Stage of the Capital
Reproduction Cycle
Economic Tools and
Technologies
Functional Role in the
Model
Expected Financial
Outcome
CAPEX Formation
(Investment Stage)
AI modelling, Digital
twins
Bio-CNG and modernisation
cost justification
Optimisation of the
structure of CAPEX
Production Stage
(Operational
Efficiency)
IoT,
Predictive maintenance
Protection of fixed assets
from premature wear and
emergency shutdowns
Minimisation of
unpredictable CAPEX,
productivity growth
Logistics Stage
(Distribution and
Sales)
IoT monitoring,
Blockchain
Ensuring the quality of raw
materials and finished
products in real time
Reducing OPEX for fuel
and losses from product
defects
Market Realisation
(Value Creation)
Digital Quality
Verification, Blockchain-
Based Traceability
Certified quality and
sustainability support
premium positioning
Increased ROI, higher
profit margins, and
growth in net profit
The additional value in this model is
generated through the blockchain quality
verification mechanism, which enables
capitalising on the trust of European consumers
and receiving a premium of USD100 thousand
per year, which is critically important within the
framework of implementing the Farm-To-Fork
Strategy. The application of the developed
mathematical model for calculating ROI shows
an increase in return on capital from 20% to
35%, which directly correlates with a reduction
in the payback period of investment projects
from 5 to 2.8 years (Table 6). Thus, the
synergistic effect of digitalisation and bioenergy
autonomy ensures not only the enterprise’s
energy independence but also creates a
sustainable mechanism for optimising OPEX,
turning technological costs into a source of
strategic competitive advantage in global
markets.
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Table 6. Economic Efficiency of Implementing the Value-Chain Digital Control Model at
Lityn Dairy Plant LLC.
Indicator
Category
Calculation
Parameter
Traditional
Model (Million
USD)
Digital Model
(Million
USD)
Economic Effect
Investment
Expenditures
CAPEX 2.0 2.0
Reallocation of investments toward Bio-
CNG infrastructure, blockchain systems
and IIoT technologies without increasing
total capital expenditures.
Operating
Costs
Logistics and
Maintenance
Costs
0.50/year 0.30/year
40% reduction in operating costs
through optimised logistics, biomethane
utilisation and predictive maintenance.
Revenue
Enhancement
Premium Price
Effect
– 0.10/year
Additional revenue generated through
blockchain-based quality verification
and product traceability.
Financial
Performance
Net Profit 0.40/year 0.70/year
Increase in net profit by 75% (+0.30
million USD annually).
Capital
Efficiency
ROI (%) 20% 35%
Improvement in return on investment by
15 percentage points.
Investment
Recovery
Payback Period
(PBP)
5.0 years 2.8 years Reduction in payback period by 44%.
5. Discussion.
The sustainability of the Ukrainian dairy
sector under martial law depends directly on
how quickly processing enterprises adapt to new
technological advancements. Comparing the
territorial deformation of the industry with the
pre-war period, the identified regional
concentration of production in Vinnytsia,
Poltava, and Khmelnytskyi regions is a
strategically justified response of agribusiness to
exogenous risks. This study focuses on a
qualitative change in the investment structure,
prioritising not simply the expansion of
capacities but ensuring their deep digital
modernisation.
In the context of the theoretical
substantiation of the “farm-to-fork” model,
which builds on Czeglédi’s (2025) ideas on the
strategic importance of bioenergy in the agro-
industrial complex, supplementing them with
modern digital tools for managing capital
expenditures is essential. Unlike Kelly et al.
(2025) and Subbotina-Dubinski and Carbon
(2025), who place significant emphasis on
general financial support for innovative
development, the model we developed focuses
on technological quality verification as a direct
tool for maximising the ROI indicator.
However, it can offer an applied
mechanism to overcome the “institutional trap”
through the synergy of blockchain, the IIoT, and
artificial intelligence. Compared to existing
analogues, the main advantage of the author’s
model is the convergence of CAPEX and the
environmental component, which allows for
considering biogas infrastructure (Bio-CNG)
not as a separate environmental project, but as a
tool for radically reducing logistics operating
expenses (OPEX). Unlike standard automation
systems, the proposed architecture uses
blockchain not only to track commodity flows
but also to serve as a financial guarantor of
investment protection for a batch of raw
materials, thereby minimising the risk of
product rejection at the processing stage.
An important feature of the model is the
implementation of predictive asset protection
systems based on AI modelling and digital
twins, which enable transforming maintenance
of expensive equipment from reactive to
preventive, a critical need for Ukraine given its
limited access to imported components. In
addition, unlike rigid hierarchical management
models, our development is based on agile
management principles, ensuring high
adaptability of logistics chains to military risks
and personnel shortages.
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
53
The proposed digital architecture goes
beyond classical automation, forming a holistic
cost management ecosystem in which
technological transparency is the main driver of
domestic manufacturers’ entry into premium
European markets.
6. Conclusions.
Despite a full-scale invasion, the
agricultural sector displays adaptive resilience.
In 2024, the total milk production was 7,246.4
thousand tons. Analysis of the 2020–2024
balance revealed a significant reduction in
consumption due to migration; however, the
industrial processing volume increased by 666.7
thousand tons. In foreign trade, there has been a
transition from import dependence to increased
exports of high-value products, particularly
butter and condensed milk, indicating the
industry’s adaptation to crisis conditions.
A pronounced regional concentration of
dairy cattle breeding was identified, with
Poltava, Vinnytsia, and Khmelnytsia taking
leading positions. These regions emerged as the
main centres for attracting capital investment
(total investment in the sector reached USD
164.8 million). The territorial structure reflects
the priority given to capacity modernisation in
the central and western regions, which have
become the main bases for raw material
production, while the southern and eastern
regions are in a state of depression owing to the
destruction of infrastructure. A comprehensive
architecture for the “farm-to-fork” model was
developed based on the synergy of blockchain,
IIoT, and artificial intelligence.
The model provides end-to-end
transparency: blockchain guarantees the security
and verification of raw material origin, IoT
sensors enable real-time monitoring, and AI
modelling facilitates the implementation of
forecasting methods. These processes transform
operational activities into a managed investment
process, in which each technological link is
designed to minimise risks and protect the
intellectual capital of dairy processing
enterprises.
The combination of physical asset
management (CAPEX) with the implementation
of Bio-CNG infrastructure is a key driver of the
sustainability of dairy processing enterprises,
especially amid rising energy prices. Using
digital twins to justify investments in biogas
production enables a radical reduction in
operational logistics costs and ensures energy
independence.
Therefore, the digital modernisation of
Ukraine’s dairy sector, integrated with
principles of social and environmental
responsibility, is the only effective mechanism
for preserving capital and ensuring the
competitiveness of domestic enterprises in the
EU markets.
Conflict of Interest Statement.
The authors declare that there is no
conflict of interest.
Funding Disclosure.
This research received no external
funding.
Economics Ecology Socium e-ISSN 2786-8958
Volume 10 Issue 2 (2026) ISSN-L 2616-7107
54
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| spelling | oai:ojs2.www.ees-journal.com:article-3422026-06-30T15:36:44Z Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems Furman, Irina Revkova, Anna Biletska, Nataliia Svynous, Nadiia Biogas, Blockchain, Dairy Industry, Investment Management, Supply Chain Management. Biogas, Blockchain, Dairy Industry, Investment Management, Supply Chain Management. Background. Logistical gaps and territorial deformations of production capacities create unprecedented challenges for the dairy industry. This requires modernising capital investment management by transitioning to strategic investment in intelligent control systems, revising financial mechanisms, and integrating environmental sustainability into the “from farm to fork” concept to ensure enterprise viability. Purpose. The purpose is to substantiate the development of a model for capital investment management by integrating end-to-end digital technologies into the “farm-to-fork” value chain, combining physical asset management (CAPEX) with the implementation of biogas (Bio-CNG) infrastructure. Findings. Analysis of the dynamics of gross milk production and investment activity in Ukraine in 2020–2024 revealed a deep structural transformation of the dairy market, characterised by a transition to intensive business models and the redistribution of production capacities toward the western and central regions. The strategic architecture of investment support enabled the formation of a holistic system of digital control over capital investments, ensuring the transition from spontaneous capacity renewal to strategic management of financial resources and increased enterprise competitiveness in the global dairy market. The use of AI-based predictive maintenance and digital twins optimises CAPEX and reduces OPEX by integrating renewable energy (Bio-CNG) into the logistics chain. The proposed model demonstrates how digital transparency creates premium value for products through eco-labelling and blockchain verification. The implementation of the Value-Chain Digital Control Model ensured a 75% increase in net profit, an increase in return on investment from 20% to 35% (by 15 percentage points), and a 44% reduction in the payback period (from 5 to 2.8 years). Implication. The dairy sector demonstrates adaptive resilience, with a trend toward producing high-value-added products for export. The developed digital architecture “from farm to fork” (Blockchain and Internet of Things) provides end-to-end quality control and protection of intellectual capital. The integration of bio-CNG infrastructure is a critical driver of energy independence and reduced logistics costs. Digital modernisation, combined with social and environmental responsibility, is identified as a priority mechanism for ensuring the competitiveness of Ukrainian dairy enterprises in the EU markets. Background. Logistical gaps and territorial deformations of production capacities create unprecedented challenges for the dairy industry. This requires modernising capital investment management by transitioning to strategic investment in intelligent control systems, revising financial mechanisms, and integrating environmental sustainability into the “from farm to fork” concept to ensure enterprise viability. Purpose. The purpose is to substantiate the development of a model for capital investment management by integrating end-to-end digital technologies into the “farm-to-fork” value chain, combining physical asset management (CAPEX) with the implementation of biogas (Bio-CNG) infrastructure. Findings. Analysis of the dynamics of gross milk production and investment activity in Ukraine in 2020–2024 revealed a deep structural transformation of the dairy market, characterised by a transition to intensive business models and the redistribution of production capacities toward the western and central regions. The strategic architecture of investment support enabled the formation of a holistic system of digital control over capital investments, ensuring the transition from spontaneous capacity renewal to strategic management of financial resources and increased enterprise competitiveness in the global dairy market. The use of AI-based predictive maintenance and digital twins optimises CAPEX and reduces OPEX by integrating renewable energy (Bio-CNG) into the logistics chain. The proposed model demonstrates how digital transparency creates premium value for products through eco-labelling and blockchain verification. The implementation of the Value-Chain Digital Control Model ensured a 75% increase in net profit, an increase in return on investment from 20% to 35% (by 15 percentage points), and a 44% reduction in the payback period (from 5 to 2.8 years). Implication. The dairy sector demonstrates adaptive resilience, with a trend toward producing high-value-added products for export. The developed digital architecture “from farm to fork” (Blockchain and Internet of Things) provides end-to-end quality control and protection of intellectual capital. The integration of bio-CNG infrastructure is a critical driver of energy independence and reduced logistics costs. Digital modernisation, combined with social and environmental responsibility, is identified as a priority mechanism for ensuring the competitiveness of Ukrainian dairy enterprises in the EU markets. Dr. Viktor Koval 2026-06-30 Article Article Peer-reviewed Article application/pdf https://ees-journal.com/index.php/journal/article/view/342 10.61954/2616-7107/2026.10.2-3 Economics Ecology Socium; Vol. 10 No. 2 (2026): Economics Ecology Socium; 39-55 Економіка Екологія Соціум; Том 10 № 2 (2026): Economics Ecology Socium; 39-55 2616-7107 2616-7107 10.61954/2616-7107/2026.10.2 en https://ees-journal.com/index.php/journal/article/view/342/294 Copyright (c) 2026 Economics Ecology Socium https://creativecommons.org/licenses/by-nc/4.0 |
| spellingShingle | Biogas Blockchain Dairy Industry Investment Management Supply Chain Management. Furman, Irina Revkova, Anna Biletska, Nataliia Svynous, Nadiia Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title | Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title_alt | Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title_full | Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title_fullStr | Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title_full_unstemmed | Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title_short | Value-Chain Digital Control Model of Capital Investment Optimisation and Quality Assurance in Farm-To-Fork Systems |
| title_sort | value-chain digital control model of capital investment optimisation and quality assurance in farm-to-fork systems |
| topic | Biogas Blockchain Dairy Industry Investment Management Supply Chain Management. |
| topic_facet | Biogas Blockchain Dairy Industry Investment Management Supply Chain Management. Biogas Blockchain Dairy Industry Investment Management Supply Chain Management. |
| url | https://ees-journal.com/index.php/journal/article/view/342 |
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