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Citation: Aleksieva, V.; Valchanov, H.;
Maleshkov, V.; Haka, A. Blockchain
Solutions for Logistic Management.
Blockchains 2024,2, 445–457. https://
doi.org/10.3390/blockchains2040019
Academic Editors: Keke Gai and
Liehuang Zhu
Received: 24 July 2024
Revised: 16 October 2024
Accepted: 28 October 2024
Published: 31 October 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
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4.0/).
Article
Blockchain Solutions for Logistic Management
Veneta Aleksieva * , Hristo Valchanov , Venelin Maleshkov and Aydan Haka
Faculty of Computer Sciences and Automation, Technical University of Varna, 9010 Varna, Bulgaria;
hristo@tu-varna.bg (H.V.); v.maleshkov@tu-varna.bg (V.M.); aydin.mehmed@tu-varna.bg (A.H.)
*Correspondence: valeksieva@tu-varna.bg
Abstract: Blockchain technologies have the potential to fundamentally change logistics and supply
chain management. By leveraging the capabilities of blockchain technology, businesses can increase
efficiency, reduce costs, and improve security and trust in operations. However, there are still
difficulties to overcome in terms of uptake and implementation. This article examines the various
blockchain technologies applicable in the field of logistics, presents the benefits and limitations of
blockchain technologies in this aspect, and offers a summary of the existing technologies used in the
logistics sector. According to this, blockchain-based models applicable both to a specific stage of the
logistics process (e.g., transportation of goods, materials, and feedstocks; management of warehouse
operations; cargo tracking; etc.) and related insurance services have been proposed. The proposed
models have been tested in a lab environment on the HyperLedger Fabric platform, and the results
show that they are fully functional.
Keywords: blockchain; HyperLedger Fabric; logistics; hierarchical model; blockchain-based
logistic model
1. Introduction
With the appearance of smart contracts in blockchain technologies and the first regula-
tions with standards in Ethereum (ERC20, ERC223, ERC777, ERC1820, and ERC721) [
1
–
5
]
guaranteeing the correct operation of the smart contract code, applications of blockchain
technology for various business solutions are beginning. This goes beyond the previously
imposed notion that blockchain technologies are only suitable for cryptocurrencies and
challenges both science and business to find solutions based on blockchains and smart con-
tracts that improve existing solutions in various aspects: security of transactions, anonymity
of participants in the network, accessibility of the information, transparency of processes
for all participants, irreversibility of recorded events/data, possibility to record different
type and format of data, encryption of data, time-stamped transactions, and impossibility
of tampering with already recorded data.
The blockchain-based solutions offer workflow with trusted data, end-to-end visibility,
and automation to multiple organizations and industries. The solutions change the flow
of data from centrally designed and resource-intensive products to knowledge-intensive
decentralized services designed and produced with strong support from advanced analytics
and artificial intelligence. The techniques of collective intelligence, artificial intelligence,
advanced analytics, big data, digital transformation, and service design are good examples
of innovative technologies applied from global business leaders. The blockchain-based
solutions are also innovative direction to change the business toward new horizons. But
not every business is suitable for implementing blockchain-based solutions. At different
adoption stages like research, pilot, development, and production, companies are setting
their footprints with this burgeoning technology, but more than 30 solutions are fully
functional. According to 2021 statistics [
6
] for 100 companies, 81 of them are ready to try
blockchain-based solutions. If we read a popular statistic on [
7
], 30 examples of blockchain
solutions are presented.
Blockchains 2024,2, 445–457. https://doi.org/10.3390/blockchains2040019 https://www.mdpi.com/journal/blockchains
Blockchains 2024,2446
The crypto API platform, Node as a Service (NaaS), has been launched as Blockchain as
a Service (BaaS) on Microsoft Azure since 2018, offering paid applications (crypto APIs) for
it based on Ethereum [
8
]. Thus, with the help of the hybrid cloud capabilities of Microsoft
Azure, customers are provided with new blockchain services that can simplify their complex
business processes. The daily emergence of cryptocurrencies and the introduction of
blockchain-based pilot solutions require society to establish a legal framework to protect
the participants of blockchain-based solutions. The EU Parliament published in 2023
the first EU rules to trace crypto-asset transfers for customer protection [
9
]. Since 2018,
the first public sector blockchain infrastructure in Europe has been created, European
Blockchain Services Infrastructure (EBSI) [
10
]. In 2023, the European Commission launched
the European Regulatory Sandbox for Blockchain for the period 2023–2026, where up to
20 projects per year of business companies or scientific organizations will be able to test
their products and services [
11
]. All these capabilities provide developers and scientists
with a stable environment in which to create, test, and prototype various blockchain-based
business solutions.
Websites have appeared where applications using smart contracts on different blockchains
are divided into categories. One such current classification for blockchain-based applica-
tions in the logistics sector [
12
] shows that there are currently 12 active cryptocurrency
blockchains running smart contracts for solutions in this sector, while many times, more
cryptocurrencies (1483) are actively used for entertainment, such as memes. According
to [
13
], the cryptocurrency market is valued at $2.6 trillion with an average increase of
0.77% over the last day (21 July 2024). The total market cap for stablecoins is $164.6 bil-
lion. The total crypto market volume over the last 24 h is $59.3 billion, and the number
of confirmed transactions per day is 680,330 on 20 July 2024. That’s a huge amount of
data per day that needs to be stored and protected but accessible for retrieval 24/7 to be
used for reference, comparison, analysis, and trend prediction. What’s more, duplicate,
forged, and incorrect data can lead to lost revenue and compliance issues. Blockchain and
big data analytics together can ensure the authenticity of data records in larger volumes,
such as terra and zettabytes, but designers of such systems must carefully consider which
data to store, where to store it, and in what format for timely and accurate processing that
would lead to correct management decisions for the respective business. In addition, with
blockchain-based solutions, all participants in the process can make inquiries about the
status and location of the product at any time, which ensures the product’s originality
and non-substitutability along the manufacturer-to-customer chain, proving compliance
violations and delivery delays, enables immediate action to be taken during emergencies
(e.g., in the event of a product recall from the market) and is proven to ensure compliance
with regulatory requirements. In addition, by combining blockchain with Internet of Things
(IoT) technology, supply chains can automate the tracking of manufacturing, transportation,
and quality control conditions.
A reason for the slower penetration of blockchain-based solutions in the logistics sector
is that logistics is a complex and multifaceted business process in which the management
and optimization of information, material, and financial flows are carried out at all levels
and subsystems, depending on the management needs: operational, tactical, strategic,
integration, and collaboration layers. Existing automated solutions mainly focus on a
single process (e.g., only on warehouse management, transport management, open area
management, or material requirements planning) to ensure the continuity of the production
process, management of forwarding, and so forth. Automated solutions require the use
of technologies for automatic identification of units: commercial, logistical, and locations.
Practice has proven barcodes (or QR codes) and RFID to be the most suitable data carriers
for fast processing with minimal human error. Nowadays, a common approach is to
use different software for different subsystems. Such systems facilitate a limited type
and number of transactions, process large volumes of data that are uniform, and allow
the output of management inquiries for the relevant subsystem. Adding automation to
another subsystem necessitates a review and redesign of existing processes to “straighten”
Blockchains 2024,2447
them into consistent flow and avoid process duplication, delays, and lack of connectivity
between processes. The correct structuring of information, goods, and financial flows when
introducing a unified information system will lead to acceleration and optimization of the
work process, a reduction of operating costs, improved traceability of goods, improved
control of task performance, and even an increase in the quality of customer service and
work with counterparties. These are precisely the advantages that blockchain technology
itself provides and is the basis of the idea of seeking blockchain-based solutions in logistics.
The proven advantages of blockchain solutions raise the question of where in auto-
mated logistics management systems they can be applied and what model is appropriate in
order to increase efficiency, reduce operational costs, enhance security and trust, and auto-
mate the tracking of production, transportation, and quality control conditions, not only by
the manufacturing company but also by its partners (insurers, forwarding companies, and
customers), allowing them to share tracking data as a means to verify product authenticity
and ensure ethical supply chain practices.
Like any new technology, blockchain is coming in smoothly and raises doubts about
whether it is cost-effective to transit from an established working solution to a blockchain-
based solution. For functions such as real-time data analysis and traceability, blockchain
creates a huge impact when combined with big data analytics and is here to assure that the
infrastructure will become more cost-effective in the near future. Blockchain technology
brings trust, transparency, security, and visibility to all participants in the business network.
These benefits outweigh skepticism about the perceived high cost of transitioning to
blockchain-based solutions.
Based on the review of existing solutions in the logistics sector and the supply chain,
this paper proposes an abstract layered model for managing logistics processes, analyzing
the possibilities of applying blockchain solutions according to this model. To prove the
applicability of the proposed hierarchical management model in blockchain-based logistics,
the authors present a management model for a logistics subsystem. This use case is
experimentally implemented on a private blockchain, HyperLedger Fabric.
The paper is organized as follows: Section 2discusses earlier work in this area.
Section 3
describes the proposed hierarchical logistic management model and presents
solutions of related works and previous authors’ works on which layer in this logistic
management model belong. Section 4presents one example of application of the pro-
posed hierarchical model through authors’ blockchain-based model of one subsystem,
namely subsystem “Process for delivery of production to a distribution warehouse”. This
solution works on HyperLedger fabric blockchain, and the results are presented and dis-
cussed. Finally, Section 5concludes the work and outlines some promising directions for
further research.
2. Related Works
A number of critical reviews of existing blockchain-based solutions in this sector have
been conducted. In [
14
], which is from the dawn of the emergence of smart contracts,
the problem with the lack of clear regulations and uniform standards for the use of these
technologies is addressed. As explained above, this problem has been solved for established
blockchains, such as Ethereum and HyperLedger Fabric, and in the last two years, the
European Parliament has been actively filling the legal gap. In [
15
,
16
], attempts are made
for the first time to analyze the applicability of blockchains in the logistics sector. At the
same time, only the advantages of blockchain technologies for any business application are
pointed out, and how they would optimize a process with many interconnected functions
and a large number of participants, without focusing on specific logistics processes or
analyzing possible patterns, are presented.
In [
17
–
38
], the already mentioned advantages of integrating blockchain technologies
into logistics processes are explained, and some key risks and challenges are indicated,
such as scalability problems due to high energy consumption, lack of standardization, and
increased costs of implementing the technology. Moreover, they analyze the changes in
Blockchains 2024,2448
the roles and functions of the different actors in supply chains and reverse logistics when
transitioning to blockchain-based solutions and integration with existing systems.
For the first time, models applicable to any subsystem of a logistics process or supply
chain appeared in 2018. The first attempts are aimed at the operational level of logistics,
reverse logistics or warehouse inventory management [
39
–
42
]. Most of them are only
at the conceptual level—architecture, analytical/mathematical model, interaction model,
and distribution of roles and functions in a separate subsystem or specific business—
without a test, prototype, or pilot proof of their workability with an implementation on a
specific blockchain.
Proposed models for logistics process subsystems using IoT (RFID) are also initially
proposed at a conceptual level [
43
–
46
], while in [
47
–
52
], the proposed models are tested on
a specific blockchain but offer optimization of only one process. Models that cover several
subsystems are proposed in [
53
–
55
], but they also offer logistics management within a
specific business sector.
In [
56
–
60
], pilot applications using blockchains for various subsystems of the logistics
process or businesses with a short life cycle are proposed. They are implemented with
smart contracts on Ethereum and derivative blockchains. And in [
61
], a model is proposed
but tested on a private blockchain, HyperLedger Fabric. The most implemented solutions
in the field of logistics and supply chain are based on Ethereum, HyperLedger Fabric, and
IOTA due to the specific role of the blockchain in the specific solution. The most common
subsystems of the logistics process are related to inventory management [
42
,
45
,
52
,
56
,
62
,
63
],
which are part of warehouse management as a whole [39–42,45,47,52,56,61–64].
Based on the analysis, Table 1presents the most commonly used blockchain technolo-
gies applicable in the field of logistics. For greater security and privacy, private blockchains
are preferred, while for payment-related applications requiring quick and easy approval,
public blockchains with smart contracts are chosen. All blockchain technologies presented
here achieve scalability but use different techniques to track goods and transactions.
Table 1. Blockchain Technologies Applicable in Logistics Processes.
Blockchain
Name Ethereum HyperLedger
Fabric Corda Sweetbridge IOTA VeChainThor
Access of peers
on the Network Public Private Private - Public Public
Consensus
mechanism PoW/PoS
PBFT,
Kafka,
Raft
Optionally
Dual
token
model
DAG PoA
Security Ethash
SHA-256,
P-256,
RSA
SHA-256 SHA-256 Troika SHA-256,
ECDSA
Smart contracts Yes Yes Yes No No Yes
Cryptocurrency Ether No No Sweetcoin
Bridgecoin IOTA VET
Scalability Yes Yes Yes Yes Yes Yes
Traceability Yes Yes Yes Yes Yes Yes
Existing
solutions-test,
pilot,
implemented
Viant,
Modum,
Provenance
IBM FoodTrust,
ChainTrack,
PharmaChain
CordaTrack,
AgriChain,
LiquorLens
Sweetbridge
IoTrace,
IoTangle
Logistics,
SmartChain
Iota
VeChain
The choice of the blockchain platform for logistics processes and supply chains largely
depends on the needs of the business: speed, privacy, programmability, or efficiency. There
are other blockchain technologies suitable for various aspects of logistics processes, but they
Blockchains 2024,2449
do not yet offer commercial or pilot solutions and are still at the lab prototype stage. The
continuous development and improvement of blockchain technologies promise businesses
increasingly flexible and adaptable solutions, addressing the shortcomings of traditional
solutions without the application of blockchain technologies.
Table 2presents automated solutions for logistics processes by different subsystems of
the logistics process. The proposed blockchain-based models of the authors of this article are
presented in a separate column. They also do not cover all logistics subsystems and focus
on developing models for not particularly complex processes that allow tracking with IoT.
It is noteworthy that in all the considered decisions, a clear hierarchy in decision-making in
the overall logistics process and supply chains is not presented.
Table 2. Solutions for Logistic Management of Subsystems.
Logistic Subsystem Examples
Without Blockchain
Examples
With Blockchain
Authors’
Blockchain-Based Models
Production or
specific process [16] [44] [65–68]
Warehouse [42,64] [47,61] [69]
Distribution [50]- -
Inventory [41,43,45,63] [39,40,42,52,56,62,63] [70,71]
Transport [53,58] [17,33,48] [72]
Information and control [43,45] [49,59] [70,71]
Reverse [39,51] [36,40]-
Management [43] [41,46,59,61]-
3. Proposed Hierarchical Logistic Management Model
In Table 3, logistics management is presented at four hierarchical levels in terms of
decision-making and the type and volume of data processed. The first level (operational
layer) refers to the physical work associated with the goods: warehousing, packaging,
order processing, and inventory control. The largest volume of data is generated here, and
IoT technologies can be used, such as QR tags and RFID. The second level (tactical layer)
separates the activities related to the transport of the goods: planning the route, analyzing
the transport costs, and optimizing the work process through cross-docking. The strategic
level (strategic layer) is suitable for the integration of new technologies, risk management,
and planning of the entire logistics network connected to third parties (insurers, distribu-
tors, suppliers, and customers). The highest level (integration and collaboration layer) is
related to improving the overall process, making strategic decisions based on the results
obtained from the analyzed information from the lower levels, implementing innovative
technologies to improve logistics processes by forecasting deliveries, optimizing storage
areas, inventory management, entering new markets, and so forth. The presented hierarchi-
cal scheme detects the gaps in the existing solutions and provides an opportunity for new
fragmentation of processes and creation of new information flows along the management
hierarchy, leading to reduction of duplication of processes, minimization of delays from
incorrect planning, and clearer forecasting.
Existing solutions based on blockchains mainly solve problems at the bottom two
levels of the model: operational and tactical. The most intuitive approach when switching
to an automated management system is to take the layered approach. On the operational
layer, where the material and financial flows occur and large volumes of data are generated,
systems are applied to process these routine operations in order to minimize human
errors, speed up material and financial flows, and ensure interaction between different
departments and business partners.
The main purpose of these systems is to facilitate the control and management of
day-to-day core logistics activities. The data generated at this level have large volumes
and high levels of detail. They should be reworked into references and summarized
Blockchains 2024,2450
when used by upper-level managers. At this level, management decisions can be made
based on the analysis of employee productivity, useful working hours, volume of material
flows, densification of storage areas, environmental control in warehouses, packaging,
management of internal transport, and so forth. Thus, at the operational level, automated
systems can be considered at two sublevels: the level of transactions (where data is collected)
and the level of management of individual subsystems.
Table 3. Hierarchical Logistic Management.
Layer Focus Example
4. Integration and
collaboration layer
Analytics and data-driven decision-making
Integrating management systems
Customer relationship management and service quality
Innovation in logistics services
[57]
3. Strategic layer
Logistic network design
Strategic partner and third-party logistics relationships
Technology integration (IoT, RFID, QR)
Risk management
[41,43,45,46,48,49,59,61]
2. Tactical layer
Route optimization
Transportation cost analysis and freight auditing
Cross-docking
[17,33,48,53,69]
1. Operational layer
Warehousing and storage
Order fulfillment and distribution
Packaging and handling
Inventory control and management
[39,40,42,47,52,56,61,63,65,
68,70–72]
In the proposed hierarchical model, presented in Figure 1, these basic functions are at
the lowest level, transaction processing system, and are reduced to delivery of materials,
production, warehouse management, sales representative, and shipping. The chosen gran-
ularity is low, and each subsystem can be divided into stages and subsystems depending
on the complexity of the specific business in which logistic management is applied.
Blockchains 2024, 2, FOR PEER REVIEW 6
Risk management
2. Tactical layer
Route optimization
Transportation cost analysis and freight auditing
Cross-docking
[17,33,48,53,69]
1. Operational layer
War eh ou si ng and storage
Order fulfillment and distribution
Packaging and handling
Inventory control and management
[39,40,42,47,52,56,61,
63,65,68,70–72]
Existing solutions based on blockchains mainly solve problems at the boom two
levels of the model: operational and tactical. The most intuitive approach when switching
to an automated management system is to take the layered approach. On the operational
layer, where the material and financial flows occur and large volumes of data are gener-
ated, systems are applied to process these routine operations in order to minimize human
errors, speed up material and financial flows, and ensure interaction between different
departments and business partners.
The main purpose of these systems is to facilitate the control and management of
day-to-day core logistics activities. The data generated at this level have large volumes
and high levels of detail. They should be reworked into references and summarized when
used by upper-level managers. At this level, management decisions can be made based on
the analysis of employee productivity, useful working hours, volume of material flows,
densification of storage areas, environmental control in warehouses, packaging, manage-
ment of internal transport, and so forth. Thus, at the operational level, automated systems
can be considered at two sublevels: the level of transactions (where data is collected) and
the level of management of individual subsystems.
In the proposed hierarchical model, presented in Figure 1, these basic functions are
at the lowest level, transaction processing system, and are reduced to delivery of materi-
als, production, warehouse management, sales representative, and shipping. The chosen
granularity is low, and each subsystem can be divided into stages and subsystems de-
pending on the complexity of the specific business in which logistic management is ap-
plied.
Delivery of
Materials Production Warehouse
Manageament
Sales
Representative
Shipping
Transaction
Processing
System
Management
Information
System
Decision
Support System
Strategic
Management
System
Densification
of Storage
Areas
Employee
Productivity
Volume and
Weight of
Material Flows
Inventory
Management
Working
Time
Analysis
Goods
Analysis
Availability
Analysis
Order
Forecast ing
CRM
ERP
WEB
Figure 1. Proposed hierarchical logistic management model.
Blockchains 2024,2451
At the second level, management information system, tactical decisions are made for
the company. They are based on the aggregated information from the lower level. They
do not track all data in detail, but only certain indicators that guarantee stock security of
sales, process continuity, inventory management, and delivery delays and are reduced
to densification of storage areas, employee productivity, volume, and weight of material
flows. Enterprise resource planning (ERP), customer relationship management (CRM), and
website systems operate on these two levels.
At the third level, decision support system, there are systems that support decision-
making by the top managers at a strategic level. In the proposed model, these systems are
divided into subsystems such as inventory management, working time analysis, goods
analysis, and order forecasting.
At the fourth level, strategic management system, no subsystems are presented because
at this level, the systems are complex and work with different sources. These systems
are related to optimization tasks, such as determining the type, number, and locations of
distribution centers. Here, many tasks are relative to the details of the specific business and
planning and forecasting strategic decisions, such as entering new markets with existing
products or developing new products and so forth.
The proposed model outlines which data can be processed in real time, which can be
stored as big data (e.g., Cloud-Edge solution) and which should be stored on the blockchain,
depending on which level managers will use them and which subsystem they will be part
of. Blockchain solutions are best suited for the bottom two levels, with separate links
to third-level subsystems. Artificial intelligence systems are suitable for the upper two
levels of the model, decision support system and strategic management system, while
IoT technologies (QR tags, barcodes, and RFIDs) are only suitable for the lowest level,
transaction processing system.
In our paper [
70
], we have analyzed existing abstract models (related works) and
have proposed an abstract model for logistics based on blockchain and IoT. In the current
paper, based on the idea from [
70
], we have mainly focused on the logistics management
to propose a new abstract model. The model in [
70
] is oriented to the integration of two
technologies (blockchain and IoT), and it is fine-grained layered, as it focuses on physical
implementation, protocols, consensus mechanisms, and so forth. This makes it applicable
in various industrial fields, not only in logistics. In [
70
], we have presented a use case of
the logistics model based on blockchain and IoT, but in the context of tracking and proving
events, not in the context of logistic processes management.
The current proposed layered model presents another cut of abstraction, which trans-
forms the logistics process management through the prism of blockchain technology. It
differs from the traditional model of management and control in logistics processes because
it provides the opportunity for different levels of management to access through smart
contracts only the data that is necessary to make a decision at the corresponding level. The
proposed abstract model can be adapted to different specific domains. But for each of these
areas, there may be different limitations of the model that can be subjectively interpreted
as shortcomings.
Based on the proposed model, complex blockchain-based systems can be built, and
following the model ensures that no business-essential processes will be omitted during
the automation of management and there will be no duplicate, forged, or missing data.
4. Proposed Blockchain-Based Model of One Logistic Management Subsystem
To investigate the applicability of the proposed hierarchical model, the authors chose
a linear supply chain process implemented with one subsystem, “Process for delivery of
production to a distribution warehouse”. This subsystem belongs to the first layer of the
proposed hierarchical model, transaction processing system, delivery of production.
The process is linear (separate stages cannot be performed simultaneously) and is
presented in Figure 2with five subprocesses: packaging, labeling, production warehouse,
shipping, and storage. The manufactured product is packaged, labeled with product
Blockchains 2024,2452
information, and moved to the manufacturer’s warehouse, where it awaits shipping to
a distribution/sales site. This process is automated with smart contract management on
a private blockchain, HyperLedger Fabric (HF), so all users of the recorded data in the
blockchain (with the exception of the insurer) are internal to the company. This use case
was experimentally implemented on a private blockchain, but because it is implemented
on only one channel, the same model can be implemented on a public blockchain (e.g., the
most popular, Ethereum) that works with smart contracts. The authors’ choice of a private
blockchain is dictated by the advantages of a private blockchain: it guarantees lower costs
and shorter transaction validation times than a public blockchain. It is readable/writeable
only by its owner, which reduces the risk of tampering with data, reduces the risk of
attacks, and provides increased privacy (since read permissions can only be granted to
selected nodes).
Blockchains 2024, 2, FOR PEER REVIEW 8
The process is linear (separate stages cannot be performed simultaneously) and is
presented in Figure 2 with five subprocesses: packaging, labeling, production warehouse,
shipping, and storage. The manufactured product is packaged, labeled with product in-
formation, and moved to the manufacturer’s warehouse, where it awaits shipping to a
distribution/sales site. This process is automated with smart contract management on a
private blockchain, HyperLedger Fabric (HF), so all users of the recorded data in the
blockchain (with the exception of the insurer) are internal to the company. This use case
was experimentally implemented on a private blockchain, but because it is implemented
on only one channel, the same model can be implemented on a public blockchain (e.g., the
most popular, Ethereum) that works with smart contracts. The authors’ choice of a private
blockchain is dictated by the advantages of a private blockchain: it guarantees lower costs
and shorter transaction validation times than a public blockchain. It is readable/writeable
only by its owner, which reduces the risk of tampering with data, reduces the risk of at-
tacks, and provides increased privacy (since read permissions can only be granted to se-
lected nodes).
Figure 2. Process for delivery of production to a distribution warehouse.
HyperLedger Fabric supports several programming languages for creating smart
contracts: Java, Typescript, and Go. The current implementation uses the Go language. It
is an agent-based language where objects are viewed as self-operating modules that inter-
act with each other to solve complex problems. Its interaction with the blockchain network
built through HF is done through the Shim library, which is standard library for Go lan-
guage, and provides an interface of classes and components for implementing smart con-
tracts. Through it, transactions to the network and access to other smart contracts (called
chain codes in the HF context) in the system are carried out.
Figure 3 shows the implementation of the presented model as an HF network. In the
blockchain (Channel1), information about the goods that are subject to forwarding and
storage is recorded. Each good (object) is characterized by aributes:
• TypeOfGoods—the type of goods.
• ProductionDate—production date.
• ExpiryDate—expiration date.
• Weight—weight of the goods.
• Number—quantity of the goods.
• Temperature—storage temperature.
• Humidity—storage humidity.
Labelling
Packaging Production
Warehouse Shipping Storage
Figure 2. Process for delivery of production to a distribution warehouse.
HyperLedger Fabric supports several programming languages for creating smart
contracts: Java, Typescript, and Go. The current implementation uses the Go language.
It is an agent-based language where objects are viewed as self-operating modules that
interact with each other to solve complex problems. Its interaction with the blockchain
network built through HF is done through the Shim library, which is standard library
for Go language, and provides an interface of classes and components for implementing
smart contracts. Through it, transactions to the network and access to other smart contracts
(called chain codes in the HF context) in the system are carried out.
Figure 3shows the implementation of the presented model as an HF network. In the
blockchain (Channel 1), information about the goods that are subject to forwarding and
storage is recorded. Each good (object) is characterized by attributes:
•TypeOfGoods—the type of goods.
•ProductionDate—production date.
•ExpiryDate—expiration date.
•Weight—weight of the goods.
•Number—quantity of the goods.
•Temperature—storage temperature.
•Humidity—storage humidity.
Blockchains 2024, 2, FOR PEER REVIEW 9
Figure 3. Blockchain-based solution of the proposed model for delivery of production.
The model contains several participants (organizations): Warehouse Manager (Org1),
Inventory Management Manager (Org2), Sales Manager (Org3), Order Forecasting Man-
ager (Org4), and Insurer (Org5). Warehouse Manager (Org1) has full control over the
channel for writing and reading information. Only this peer can enter information into
the blockchain. It is from the first level of the hierarchical logistic management model.
Inventory Management Manager (Org2) is responsible for maintaining a sufficient
amount of stock. It is from the third level of the hierarchical logistic management model.
Sales Manager (Org3) is responsible for the sale of the product and maintaining relations
with the sales representatives. It is from the first level of the hierarchical logistic manage-
ment model. Order Forecasting Manager (Org4) analyzes consumer demand and predicts
trends in product realization. It is from the third level of the hierarchical logistic manage-
ment model. Insurer (Org5) will use the information stored in the blockchain in case of an
insurance event. It is from the third level of the hierarchical logistic management model.
Solid lines represent organizations’ access to the channel. Peers relevant to the organ-
ization implement read/write operations, and they are shown as dashed lines.
The business logic of the model is implemented by the smart contract (name in HF is
“codechain”). It includes multiple objects and functions that provide the API to access the
blockchain. Individual peers are implemented as Docker containers (Figure 4). This allows
achieving the encapsulation of individual nodes within the execution run-time environment.
Figure 4. Implementation of the network with Docker containers.
Figure 3. Blockchain-based solution of the proposed model for delivery of production.
Blockchains 2024,2453
The model contains several participants (organizations): Warehouse Manager (Org1),
Inventory Management Manager (Org2), Sales Manager (Org3), Order Forecasting Man-
ager (Org4), and Insurer (Org5). Warehouse Manager (Org1) has full control over the
channel for writing and reading information. Only this peer can enter information into
the blockchain. It is from the first level of the hierarchical logistic management model.
Inventory Management Manager (Org2) is responsible for maintaining a sufficient amount
of stock. It is from the third level of the hierarchical logistic management model. Sales
Manager (Org3) is responsible for the sale of the product and maintaining relations with the
sales representatives. It is from the first level of the hierarchical logistic management model.
Order Forecasting Manager (Org4) analyzes consumer demand and predicts trends in
product realization. It is from the third level of the hierarchical logistic management model.
Insurer (Org5) will use the information stored in the blockchain in case of an insurance
event. It is from the third level of the hierarchical logistic management model.
Solid lines represent organizations’ access to the channel. Peers relevant to the organi-
zation implement read/write operations, and they are shown as dashed lines.
The business logic of the model is implemented by the smart contract (name in
HF is “codechain”). It includes multiple objects and functions that provide the API to
access the blockchain. Individual peers are implemented as Docker containers (Figure 4).
This allows achieving the encapsulation of individual nodes within the execution run-
time environment.
Blockchains 2024, 2, FOR PEER REVIEW 9
Figure 3. Blockchain-based solution of the proposed model for delivery of production.
The model contains several participants (organizations): Warehouse Manager (Org1),
Inventory Management Manager (Org2), Sales Manager (Org3), Order Forecasting Man-
ager (Org4), and Insurer (Org5). Warehouse Manager (Org1) has full control over the
channel for writing and reading information. Only this peer can enter information into
the blockchain. It is from the first level of the hierarchical logistic management model.
Inventory Management Manager (Org2) is responsible for maintaining a sufficient
amount of stock. It is from the third level of the hierarchical logistic management model.
Sales Manager (Org3) is responsible for the sale of the product and maintaining relations
with the sales representatives. It is from the first level of the hierarchical logistic manage-
ment model. Order Forecasting Manager (Org4) analyzes consumer demand and predicts
trends in product realization. It is from the third level of the hierarchical logistic manage-
ment model. Insurer (Org5) will use the information stored in the blockchain in case of an
insurance event. It is from the third level of the hierarchical logistic management model.
Solid lines represent organizations’ access to the channel. Peers relevant to the organ-
ization implement read/write operations, and they are shown as dashed lines.
The business logic of the model is implemented by the smart contract (name in HF is
“codechain”). It includes multiple objects and functions that provide the API to access the
blockchain. Individual peers are implemented as Docker containers (Figure 4). This allows
achieving the encapsulation of individual nodes within the execution run-time environment.
Figure 4. Implementation of the network with Docker containers.
Figure 4. Implementation of the network with Docker containers.
Each Docker container runs as a stand-alone node. As seen in Figure 4, the commu-
nication between the nodes is based on the TCP/IP protocols. This enables a distributed
implementation of the model.
Experimental tests of the functionality of the smart contract have been conducted. For
this purpose, an administrative Docker node was created, which allows the execution of
commands through which requests are sent to the smart contract. Requests perform certain
functions of its API. Figure 5shows the execution of a request to write in the blockchain
information about a certain goods (Coffee) with corresponding values of its attributes.
Query executions are in DEBUG mode for detailed analysis. Successful completion is
determined by the correct result code, 200.
All peers except Peer0 can only read data from the blockchain. Figure 6shows the
execution of a request to find a record(s) for corresponding goods. In this case, search is
made by name (Coffee). Upon successful execution of the search query, the attributes of the
found goods are displayed.
Blockchains 2024,2454
Blockchains 2024, 2, FOR PEER REVIEW 10
Each Docker container runs as a stand-alone node. As seen in Figure 4, the commu-
nication between the nodes is based on the TCP/IP protocols. This enables a distributed
implementation of the model.
Experimental tests of the functionality of the smart contract have been conducted. For
this purpose, an administrative Docker node was created, which allows the execution of com-
mands through which requests are sent to the smart contract. Requests perform certain func-
tions of its API. Figure 5 shows the execution of a request to write in the blockchain infor-
mation about a certain goods (Coffee) with corresponding values of its attributes.
Figure 5. Write a record into the channel.
Query executions are in DEBUG mode for detailed analysis. Successful completion
is determined by the correct result code, 200.
All peers except Peer0 can only read data from the blockchain. Figure 6 shows the
execution of a request to find a record(s) for corresponding goods. In this case, search is
made by name (Coffee). Upon successful execution of the search query, the aributes of
the found goods are displayed.
Figure 6. Search for object in the blockchain.
The tests proved the functionality of the proposed model.
5. Discussion
Automated process management with or without blockchain solutions is a complex
and multifaceted process that cannot be formalized into a few universal solutions. The
possibilities of combining blockchain technologies with other innovative technologies,
such as artificial intelligence or the IoT, provide the potential to achieve greater efficiency
and optimization of logistics processes. Currently, more than 30 global companies have
fully functional products built on blockchain. For functions such as real-time data analysis
and traceability, blockchain has a significant impact, especially when combined with big
data analytics.
The existing solutions are based on best practices in the specific fields and are not
focused on specific requirements of a specific business process. The participation of ex-
perts in the design of such complex systems with multiple subsystems managing inter-
connected information, financial, and material flows significantly increases the effective-
ness of the included functionalities, as the focus of complex solutions does not shift only
to a separate subsystem, for example, optimization of warehouse processes or optimiza-
tion of financial flows serving financiers, accountants, and traders.
Figure 5. Write a record into the channel.
Blockchains 2024, 2, FOR PEER REVIEW 10
Each Docker container runs as a stand-alone node. As seen in Figure 4, the commu-
nication between the nodes is based on the TCP/IP protocols. This enables a distributed
implementation of the model.
Experimental tests of the functionality of the smart contract have been conducted. For
this purpose, an administrative Docker node was created, which allows the execution of com-
mands through which requests are sent to the smart contract. Requests perform certain func-
tions of its API. Figure 5 shows the execution of a request to write in the blockchain infor-
mation about a certain goods (Coffee) with corresponding values of its attributes.
Figure 5. Write a record into the channel.
Query executions are in DEBUG mode for detailed analysis. Successful completion
is determined by the correct result code, 200.
All peers except Peer0 can only read data from the blockchain. Figure 6 shows the
execution of a request to find a record(s) for corresponding goods. In this case, search is
made by name (Coffee). Upon successful execution of the search query, the aributes of
the found goods are displayed.
Figure 6. Search for object in the blockchain.
The tests proved the functionality of the proposed model.
5. Discussion
Automated process management with or without blockchain solutions is a complex
and multifaceted process that cannot be formalized into a few universal solutions. The
possibilities of combining blockchain technologies with other innovative technologies,
such as artificial intelligence or the IoT, provide the potential to achieve greater efficiency
and optimization of logistics processes. Currently, more than 30 global companies have
fully functional products built on blockchain. For functions such as real-time data analysis
and traceability, blockchain has a significant impact, especially when combined with big
data analytics.
The existing solutions are based on best practices in the specific fields and are not
focused on specific requirements of a specific business process. The participation of ex-
perts in the design of such complex systems with multiple subsystems managing inter-
connected information, financial, and material flows significantly increases the effective-
ness of the included functionalities, as the focus of complex solutions does not shift only
to a separate subsystem, for example, optimization of warehouse processes or optimiza-
tion of financial flows serving financiers, accountants, and traders.
Figure 6. Search for object in the blockchain.
The tests proved the functionality of the proposed model.
5. Discussion
Automated process management with or without blockchain solutions is a complex
and multifaceted process that cannot be formalized into a few universal solutions. The
possibilities of combining blockchain technologies with other innovative technologies, such
as artificial intelligence or the IoT, provide the potential to achieve greater efficiency and
optimization of logistics processes. Currently, more than 30 global companies have fully
functional products built on blockchain. For functions such as real-time data analysis
and traceability, blockchain has a significant impact, especially when combined with big
data analytics.
The existing solutions are based on best practices in the specific fields and are not
focused on specific requirements of a specific business process. The participation of experts
in the design of such complex systems with multiple subsystems managing interconnected
information, financial, and material flows significantly increases the effectiveness of the
included functionalities, as the focus of complex solutions does not shift only to a separate
subsystem, for example, optimization of warehouse processes or optimization of financial
flows serving financiers, accountants, and traders.
However, at the moment, business and pilot solutions based on blockchain are only
in separate subsystems of logistics management. With regard to individual operations,
priorities are determined, and during the organization process, the correct logical sequence
of their implementation is observed, as well as optimization of the necessary resource. This
minimizes downtime, which reduces overall processing time. It is in such subsystems that
the blockchain application brings added value by minimizing operational costs and process
execution time.
This article adds value by proposing a hierarchical-layered logistics management
model, which provides insights into which subsystems the implementation of a blockchain
solution will significantly improve the efficiency of the logistics process. In addition to
this, it helps developers track which data will be used on which layers by which managers
and for what purposes. The proposed layered model guides which data is suitable for
processing with big data analysis and which for storage on blockchain and processing by
smart contracts.
A use case implemented experimentally on HyperLedger Fabric is presented. It
has been tested, and some of the results are presented. The results of the performed
Blockchains 2024,2455
experiments show that the proposed solution is fully functional in terms of managing a
logistics subsystem with a linear sequence of individual operations.
The proposed abstract layered model can be used to overcome gaps in existing logistics
process management solutions. There are many solutions (not only blockchain-based) for
transaction processing system-level management, but few solutions include multilevel
management using the same data for the managed logistic process. Moreover, they do
not include all subsystems proposed in the present abstract model. In this aspect, it is of
community interest to study the applicability of blockchain technologies specifically for
multi-aspect solutions covering more subsystems from all levels of the model.
The team’s future work is aimed at creating and testing models related to person-
nel management in the context of logistics processes. The goal is to track workplace
performance of workers, to reduce the risk during work with machines and in adverse
environments, and to increase transparency of work processes using wearable devices
and IoT. These models will refer to the decision support system layer and management
information system of the proposed hierarchical logistic management model.
Author Contributions: Conceptualization, V.A. and H.V.; methodology, V.A.; software, H.V.; vali-
dation, A.H. and V.M.; investigation, V.A., H.V., A.H. and V.M.; data curation, V.A., H.V., A.H. and
V.M.; writing—original draft preparation, V.A.; writing—review and editing, H.V., A.H. and V.M.;
visualization, H.V. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Data Availability Statement: The original contributions presented in the study are included in the
article, further inquiries can be directed to the corresponding author.
Conflicts of Interest: The authors declare no conflict of interest.
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