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POLISH MARITIME RESEARCH, No 4/2023 129
POLISH MARITIME RESEARCH 1 (117) 2023 Vol. 30; pp. 129-147
10.2478/pomr-2023-0066
STRATEGIES FOR DEVELOPING LOGISTICS CENTRES:
TECHNOLOGICAL TRENDS AND POLICY IMPLICATIONS
Minh Duc Nguyen
Faculty of Economics, Vietnam Maritime University, Haiphong, Viet Nam
Ko Tae Yeon
Heesung Electronics Vietnam Limited Company, Viet Nam
Vietnam Maritime University, Haiphong, Viet Nam
Krzysztof Rudzki
Gdynia Maritime University, Faculty of Marine Engineering, Gdynia, Poland
Hoang Phuong Nguyen
Academy of Politics Region II, Ho Chi Minh city, Viet Nam
Nguyen Dang K hoa Pham*
PATET Research Group, Ho Chi Minh City University of Transport, Ho Chi Minh city, Viet Nam
* Corresponding author: khoapnd@ut.edu.vn (Nguyen Dang Khoa Pham)
Ab str Ac t
Logistics centres are currently performing akey function in the development of countries through their ability to regulate
goods, markets, and transport. is is shown by the infrastructure, cost, goods ow, and quality of logistical services
provided by these centres. Nevertheless, in developing nations or regions with antiquated logistics infrastructure,
conventional logistics centres seem to struggle to manage the volume of commodities passing through them, resulting
in persistent congestion and an unsteady ow of goods inside these facilities. is issue poses achallenge to the
progress of any nation. e emergence of new technology oers apotential avenue to solve the problems inherent in
traditional logistics centres. Most prominently, four technologies (the Internet of ings (IoT), Blockchain, Big Data
and Cloud computing) are widely applied in traditional logistics centres. is work has conducted athorough analysis
and evaluation of these new technologies in relation to their respective functions and roles inside alogistics centre.
Furthermore, this work proposes diculties in applying new technologies to logistics centres related to issues such
as science, energy, cost, or sta qualications. Finally, future development directions, related to expanding policies
in technological applications, or combining each country’s policies for the logistics industry, are carefully discussed.
Keywords: Logistics centers, logistics infrastructure, logistical services, smart technologies
INTRODUCTION
An important topic for the growth of the world’s economy
and contemporary society is digitalisation. Continual
expansion and long-term welfare are cited as essentia l drivers
of successful digitalisation eorts. erefore, government
programmes t hat seek to develop innovation capacity, increase
productivity, decrease costs, increase revenues, improve
preparation for the digital era, and strengthen competitive
advantages are regularly used to promote digitalisation goals
within businesses. e term ‘Industry 4.0’ frequently refers
to awide range of digitalisation methods, approaches, and
technologies because it largely focuses on applications in
the industrial environment. Because of this, the application
sectors range from enhancing material ows to buildings,
manufacturing, and product development. ese programmes
should help industrial organisations achieve their objectives,
including higher competitiveness based on open processes,
more agility, improved adaption, and increased exibility.
e initial commercial practices and academic studies on
disruptive technologies are still very much relevant in today’s
POLISH MARITIME RESEARCH, No 4/2023130
society. Disruptive technologies were also the foundation
of modern business models like Amazon and Flipkart,
since they outperform incumbent technologies, in terms of
productivity, eciency, and convenience [1]. e Internet of
ings (IoT), for instance, completely replaced warehouse
and inventory management through aprecise combination of
supply hubs, transportation, and customer handling system,
which was aboost for e-commerce industries. As aresult,
IoT could oer more individualised, responsive, and novel
or unconventional customer service, in addition to decreased
operational costs [2]. e Internet of ings is anticipated to
play asignicant role in the logistics sector in the near future.
It is also evident that many objects and items have already
begun to carry or tag bar codes, RFID tags, and sensors,
bringing geospatial data and allowing tracking of avariety
of goods and merchandise through asingle supply chain
from any location [3]. Primarily, there are three schools of
thought with respect to the IoT [4]: (i) ings oriented, which
aims to improve things like object traceability and the ability
to understand their current location or status; (ii) Internet-
oriented, which seeks to improve network protocols like the
Internet Protocol, which is seen as the network technology to
connect smart objects all over the world; and (iii) Semantic
oriented, which centres on issues of meaning and context
[5]. In addition to IoT, other new technologies have also
begun to become more prominent during this period,
such as Big Data, Blockchain, AI, etc. Each technology has
dierent functions that are combined in an industry, thereby
helping the industry develop strongly in all respects [6][7].
e logistics industry is no exception to this development;
hence, the use of 4.0 technologies has transformed logistics
into astrategic tool for gaining acompetitive edge, shiing
its perception from asimple nancial burden to avaluable
asset [8]. Table 1 presents acomprehensive compilation
of denitions of Industry 4.0 technologies that have been
specically implemented in industrial environments.
Tab. 1. Denition of outstanding 4.0 technologies [9]
4.0 Technology Denition Ref
Internet of ings (IoT) e implementation of sensors and devices that are networked through wireless networks and
Internet-based interaction with the objective of enhancing the value of products and processes.
[10][11][12][13]
Blockchain e digital platform facilitates the safe storage and distribution of information across acollective of
users via the creation of time-stamped, tamper-proof, and indenitely lasting records. e system
comprises decentralised ledgers that store transactions as data blocks, which are interconnected
by acryptographic pointer. e aforementioned system exhibits attributes such as distributed
consensus, enhanced security measures, traceability, verication, and transparency of information.
[14][15][16]
Cloud Computing e online service provides users with the ability to do rapid and streamlined calculations, without
the need for establishing atangible infrastructure. is technolog y facilitates the provision of
computer resources, including networks, servers, storage, applications, and services, with the
ability to access anetwork that is readily available, easily accessible, and benecial. e outcome
is amore economically ecient and expeditious resolution with regard to operational platforms,
soware, and infrastructures.
[17][18][10]
Big Data e eective facilitation of decision-making processes is achieved via the management of
asubstantial amount of data, dened by its high volume, rapid velocity, and diversity. is is
accomplished by using cutting-edge analytic approaches that are creative in nature.
[19][20][5]
e logistics industry is showing an increasing dependence
on new technologies. erefore, in order to fully capitalise on
the potential of this industry, it is imperative to develop the
‘Logist ics 4.0’ init iative, which aims to ma ximise the uti lisation
of cutting-edge technologies and implement innovative
advancements in the logistics eld [21]. Governments should
aggressively push its ‘Logistics Centre 4.0’ strategy, starting
with the logistics centre, which serves as the beating heart
of logistics systems. As aresult, the whole manufacturing
sector, including its logistics, is transitioning to aparadigm
that is more adaptable and agile, making room for Industry
4.0. According to Khatib et al.
[22],
the heart of Industry
4.0 consists of four primary enabling technologies that will
increase the adaptability of manufacturing and distribution
processes: robotics, Big Data, wireless networking, and
inexpensive sensors. e interdependencies between the
various 4.0 technologies are depicted in Fig. 1.
POLISH MARITIME RESEARCH, No 4/2023 131
Fig. 1. Dependency between 4.0 technologies [22]
In the tech nologies mentioned above, IoT was acknowledged
as one of the most signicant elds of future technology and it
is one of the key information and communicat ion technologies
(ICT). e IoT is quickly gaining ground in the context of
contemporary wireless telecommunications, particularly
with the rapid development of wireless communication
technologies [23][24][25]. From an initial emphasis on
machine-to-machine communication and applications in
the ‘ubiquitous aggregation’ of data, the concept of IoT is
continually changing. In other words, the IoT has generated
vast amounts of data and various mathematical analytic
methods can be used to continuously investigate the intricate
links between the transactions represented by this data.
Without a doubt, IoT would be crucial to the deployment
of smart logistics [26][27], which would fundamentally alter
the design of the logistics system and the logistical operation
mode. ese changes are very important in determining
a company’s competitiveness because logistics costs are
seen as a signicant component of overall production costs.
Numerous businesses are thinking about how to operate their
warehouses more cost-eectively and eciently, especially
in light of recent advancements in supply chain and logistics
technology but there are also many businesses that are hesitant
about applying smart technologies to a previously traditional
infrastructure [28]. According to the public and academic
literature, logistics centre management is a crucial component
of the supply chain that has received increased attention,
with the aim of meeting the rising freight demand and the
increasingly high standards for logistics services[29]. In the
last few decades, the warehouse and logistics centre business
has experienced a remarkable development in major trading
cities. Planners and social scientists have expressed concerns
over the social and environmental impacts associated
with this increase. Researchers have shown that transport
infrastructure and links to supply chain partners are two of
the most important factors in luring developers to an area
[30][31]. Although t he advantages of the eects and the role of
digitalisation in logistics are still not properly recognised, it
cannot be denied that digitalisation will be an essential step in
the eld of logistics [32][33]; this is reected in transportation
and warehouse activities [34]. As a typical example, in the
past, real-time tracking of vehicles was performed using
GPS systems. en, with the advent of 4.0 technology and
blockchain, rea l-time goods track ing systems using blockchai n
technology have been applied by many companies. From
there, digital transformation frameworks are continuously
being updated, based on emerging logistics activities. e
research by Junge et al. [35] presented a framework for digital
transformation in logistics, as demonstrated in Fig. 2.
POLISH MARITIME RESEARCH, No 4/2023132
Fig. 2. e Logistics Digital Transformation Framework [35]
e next problem for the necessary development of 4.0
technologies is the e-commerce industry. e quantity of
products that need to be handled in alogistics centre has
grown over the past ten years, to meet the development of the
e-commerce industry, making warehouse operations more
complex. As aresult, older manual methods are no longer
sucient or practicable to handle this enormous amount
of activity [36]-[37]. From there, freight and logistics rms
may encounter large delays between arrival and departure,
as aresult of poor management of the logistics centre [38].
Extra fees (nes for late transportation and additional
expenditure for keeping the tractor-trailer driver on overtime)
and orders being delivered late are the direct result of this
[39]. Long lines of idle vehicles contribute to pollution [40]-
[41], thus it is best to set up transport and storage facilities
with standardised loading and warehousing eciency. e
primary objective of transportation and logistics centres
is to minimise the overall costs associated with product
transportation, while simultaneously increasing storage
capacity through the implementation of short-term strategies
and the use of technology. ese elements play acrucial role in
the ecient delivery of goods and enhancing transportation
and logistics systems [42]-[43]. Moreover, the absence of
cohesion in the managerial procedures within logistics centres
leads to frequent instances of time wastage and mistakes in
the tasks performed by personnel teams. Additionally, one
company’s barcode system will dier from their suppliers’,
leading to inconsistencies in the preservation of information
about the items’ features. is has long been aproblem in
conventional logistics centres, where it slows down the arrival
of transporting vehicles and drives up waiting times and
other expenses [44]. Because of this, the cost of logistics is
consistently high in underdeveloped nations. Precisely for
this reason, the Warehouse Management System was born to
resolve the backlog of manual operations at warehouses and
logistics centres. Warehouse Management Systems (WMS)
evolved as aresult of the emergence of increasingly complex
tools and algorithms to run warehouses eectively in the
2000s [45]. AWMS has an information system that combines
soware programmes to keep track of, regulate, control, and
manage inventory levels, and optimise warehousing choices.
Order processing, order release, and master data are the three
main WMS functions. In addition to the above functions, the
additional capabilities of WMS include receiving (inbound),
putting things away, and warehouse control [46]. However,
WMS stopped meeting the needs of traditional logistics
centres. For the e-commerce industry, specic characteristics
related to the volume and quantity of goods still make it
dicult for WMS to operate processing and storage.
By recognising the importance of technologies in
applying the management of logistics centres to asmart
environment, this work analyses and makes judgements
of Industry 4.0 applications in the intelligent management
ofogistics centres. Applications that reduce the number of
pointless procedures can lighten the load in alogistics centre.
Eciency and operational productivity are then improved.
ese applications also pave the way for future studies in the
eld of smart logistics, where systems are combined with
cutting-edge technology. However, there will be some notable
obstacles, such as the cost of deploying the technology, the
way in which the location of the logistics centre aects the
environment, and the policies for applying these technologies;
these will be of interest in future research.
POLISH MARITIME RESEARCH, No 4/2023 133
LITERATURE REVIEW
LOGISTICS CENTRE DEFINITION
According to the European Economic Interest Group
[47], alogistics centre is “the hub of agiven area where all
activities connected to transport, logistics, and products
distribution both for national and international transit are
carried out, on acommercial basis, by multiple operators”.
Facilities for storage, managing, clearing, reassembling,
disassembling, inspecting quality, oering lodging, and
providing social services are all found in logistics centres.
Logistical activities are moving from urban to rural areas
and using environmentally friendly modes of transportation,
like electric vehicles. In the maritime eld, the development
of green solutions for ships and ports or green logistic
centres is being considered as apriority, aiming to reduce
carbon emissions and mitigate climate change [48]–[50].
In industrialised nations, logistics centres are crucial for
sustainability and competitiveness, but they are also helpful
for regional development in poor nations [51].
On the other hand, Uyanik et al. [52] asserted that an
essential component of development strategy was the use of
logistics centres, which were initially developed in Europe
in the 1960s and were rst observed in the US during the
industrial revolution [53]. If such a centre was established in
conjunction with combined and intermodal transport types,
there would be innumerable advantages to doing so, including
lower prices, reduced trafc congestion, lower environmental
pollution levels, etc. However, the term ‘logistics centre’ was
never dened in the literature. According to Higgins et al.
[54] and Rimiené et al. [55], a number of terms implied a
logi stics ce ntre, including dist r ibution ce ntre , freight village,
dry port, inland port, load centre, logistics node, gateway,
central warehouse, freight/transport terminal, transport
node, logistics platform, logistics depot, and distribution
park. Furthermore, Erkayman et al. [56] also published a
concept for a logistics centre. National and international
locations, known as logistics centres, are where various
operators conduct all logistics-related activities on a for-
prot basis, including shipping and forwarding, product
distribution, material handling, storage, and other related
transactions (such as banking and insurance). To carry out
the aforementioned tasks, a logistics centre must be furnished
with the necessary public amenities. These centres must be
located near connections to highways, railways, airports,
and seaports, as well as being located outside residential
areas. Lastly, it has to be run by a single public or private
organisation [46][57].
From the perspective of multimodal transport, according
to Smail et al. [58], a logistics centre is a type of output
point structure of the supply chain that includes stages like
warehousing, distribution, and the provision of value-added
services, and storage. According to Kaynak et al. [59],
the logistics centre is a hub that combines various modes
of transportation, almost performing like a multimodal
transportation terminal, it is a crucial link in the multimodal
transportation chain, and is a structure that serves as a hub
for transportation activities among various modes of
transportation. With the birth and evolution of the phrase
‘supply chain management’, the logistics centre concept
has also altered and developed, much like the concept of
logistics itself [60][61]. Nonetheless, it is most apparent that
a logistics centre needs to have two main functions: shipping
and warehousing. These are regarded as the two most crucial
elements in setting up a basic logistics centre.
SMART LOGISTICS CENTRE
All facets of social life are being signicantly impacted
by the Industrial Revolution 4.0. Whether they want it or
not, people are impacted by the revolution every single
day. Automation, labour-saving production, lightning-fast
product speed, and consistent quality are at the core of the
fourth industrial revolution. One of the primary concerns
is the use of automation as ameans to eectively adapt to
the strategic change that aects the national economy [62].
For logistics centres, the 4.0 revolution is bringing alot of
technology to support smarter and more exible operations.
New technologies are seen as agreat support to meet the
automation needs of logistics centres. Applying technology
to logistics centres will help eectively manage the quantity,
status, and ow of goods, in terms of time and cost.
e concept of ‘smart logistics’ has emerged in recent
times, whereby advanced information technology serves as
the fundamental basis for its implementation [63]-[64]. By
processing information from all facets of logistics in real-
time and thoroughly evaluating it, contemporary integrated
logistics systems can be intelligently implemented. End-
to-end visibility, improved transportation, warehousing,
distribution processing, information services, and other
aspects of smart logistics could all result in time and
money savings. Additionally, it might be able to lessen the
environmental damage that logistics causes. However, there
are still dicult problems that must be solved before smart
logistics can be implemented. One of the outstanding issues
is the application of technology and connected activities
in alogistics centre into acomplete chain of activities, to
overcome additional time and cost. In order to full the needs
of product storage, surveillance, safety, re and explosion
detection, and more, asmart logistics centre needs IoT
equipment, such as IoT stacking shelves and an IoT inspection,
as well as amonitoring system. e same degree of automation
and network connectivity needs to be applied to machines
and tools. It is obvious that IoT will play apivotal role in the
success of these modern logistics centres. ese applications
of IoT allow for the construction of anetwork-based cyber-
logistics system that can be managed by humans. e
incorporation of intelligence, automation, and automated
choices of technology (IoT), elements of the supply chain,
and logistics 4.0 are other important topics to explore in
the Fourth Industrial Revolution [65][66]. Amodern smart
logistics centre, with intelligent goods arrangement and
POLISH MARITIME RESEARCH, No 4/2023134
inventory management systems, is shown in Fig. 3. is is the
result of the combination of many Industry 4.0 and Logistics
4.0 ideas, including driverless cars, digital connections, and
information security, with the core functions of alogistics
centre.
Fig. 3. Operations of asmart Logistics Centre [67]
To meet the needs related to the intelligence of alogistics
centre, the study by Yavas et al. [68] focused their research on
the transformation of logistics centres in industrial revolution
4.0 and identied key criteria for logistics centres in the new
industrial era. e strategy was to look at the interactions
between the operations of traditional logistics centres and
then suggest anew framework for them. e four primary
operations of logistics centres (handling management,
information management, transport management, and
warehouse management) were the basis for the twelve criteria
for logistics centre 4.0 presented in this work. ese criteria
were acknowledged as the operational criteria at the logistics
centre stated above and were linked to the four traditional
criteria in t he proposed framework [69], as illustrated inFig.4 .
e operation of a smart logistics centre is based on the use
of the latest technology, such as Big Data and IoT, to increase
its operational eciency. rough a decision support function
based on logistics data, it also aids in the development of a
managerial logistics operation plan. According to Cho [70],
Logistics Centre 4.0 is based on IoT technologies. e data is
collected and analysed using Big Data technology, the product
is stored and transported based on the knowledge obtained
through Articial Intelligence, and a smart logistics centre
system performs tasks automatically using robots. As the
variety of items that need to be processed in a warehouse
has grown over the past decade, conventional and manual
techniques for warehouse management have proved to be
unable to manage them.
Fig. 4. Aconceptual architecture for the 4.0 logistics hub [68]
POLISH MARITIME RESEARCH, No 4/2023 135
is has resulted in a rise in the use of information
technology to facilitate warehouse operations. e WMS
has evolved as more sophisticated tools and algorithms for
managing warehouses have been made available since the
turn of the 2000s [45][71]. With the advancement of both
technology and the marketplace, however, the manufacturing
of products has shied from make-to-stock (MTS) to make-
to-order (MTO), leading to a dramatic rise in the number of
commodities. As a result, new forms of warehouse technology
are being integrated with existing warehouse management
systems. In this article, a smart logistics centre is dened
as having four 4.0 technologies: IoT, Blockchain, Big Data,
and Cloud Computing. ese technologies are applied for
solving problems in logistics centres. In the next section, we
analyse and review some applications that have been, and
are being, applied at smart logistics centres. In addition,
applicable policies, development possibilities, and future
research directions will also be mentioned in this work.
APPLICATION OF 4.0 TECHNOLOGIES
INLOGISTICS CENTRES
e secret to creating asmart logistics centre is to use
cutting-edge technologies to their fullest potential. Of these,
IoT technology has emerged as atechnology with outstanding
data collection potential, helping managers to have amore
holistic view of alogistics centre [72]-[73]. To facilitate data
communication, exchange, and control among objects using
disti nct identiers, arange of informat ion sensing technolog ies
are employed. ese technologies encompass RFID, wireless
sensor networks (WSN), and machine-to-machine systems.
Additionally, embedded systems are also utilised, in
conjunction with network communication technology, to
achieve these objectives [26][74][75]. Asensor is apparatus
that identies and reacts to a certain kind of stimulus
originating from the surrounding physical milieu. e input
might include arange of environmental phenomena, such
as heat, light, motion, moisture, pressure, or other factors.
Alternatively, the data might be communicated by electronic
means over anetwork, enabling remote access for reading
or further processing [76]. e classication of sensor types
is presented in Table 2.
Connecting and collecting massive amounts of data from
sensor systems in logistics hubs is made possible by Internet of
ings applications. is data can come from many dierent
sources, such as product volume, temperature, humidity, shelf
location, etc. According to Uckelmann et al. [85], the IoT is
dedicated to connecting the physical world to the virtual
internet and its primary drivers of development are object
self-identication, information sharing, and interactive
processing. Machine-to-machine and human-to-machine
interactions are made possible by IoT applications [86]. e
technological components of the IoT have been extensively
discussed in Miorandi et al. [87], Mishra et al. [88], Ng et al.
[89], Whitmore et al. [90], and Li et al. [91]. Despite the fact
that several types of smart logistics exist due to dierent
priorities, all of them rely on the use of ICTs. A new working
concept of smart logistics is centred on the movement of
goods, based on cutting-edge technology and intelligent
management. Fig. 5 shows the concept map of a smart logistics
centre with four technologies in the current industry 4.0 era:
IoT, Big Data, Blockchain, and Cloud computing [92].
Tab. 2. Classication of sensors [77]
Type of sensor Function Ref
GPS sensors e objective of this sensor is to determine the location of various components and to accurately detect
and communicate the operational duration of equipment in the logistics centre.
[78][79][80]
Strain sensors Quantify the instantaneous deformation experienced by structural components in atimely manner. [81]
Accelerometer sensors is particular sensor is capable of detecting changes in gravitational acceleration, enabling
themeasurement of tilt, vibration, and acceleration.
[78][79]
Barometric sensors Barometric pressure sensors have been employed in many electronic devices such as smartphones, smart
watches, and drones, to monitor air pressure readings and changes in altitude.
[78][79][82]
Wind-sensor, rain-sensor e objective is to observe and measure the velocity of wind, as well as the amount of precipitation. [83]
Fibre optic sensor e automation of operations might be achieved by the activation of the reader for RFID and GPS detectors. [84]
Laser sensor e objective is to ascertain the duration required for the production process of the equipment. [78]
Fig. 5. Intelligent logistics: aconceptual roadmap [92]
POLISH MARITIME RESEARCH, No 4/2023136
INTERNET OF THINGS IOT
One potentially useful technology that might be included
in astandard logistics system is the Internet of ings (IoT).
Utilising Auto-ID methods, such as Barcode and Radio
Frequency Identication (RFID), the IoT can accurately
identify awide range of things. e IoT would gather and
record data in real-time from awide variety of things,
allowing for real-time visibility and traceability [93]. Data
collected in real-time might be used for complex tasks like
logistics route planning. e logistics sector has recently
looked at wearable gadgets that combine IoT technology [94].
Logistics platforms have included state-of-the-art technology
to allow for automated tracking of commodities and improved
capabilities for logistics personnel [95]-[96]. With the help of
IoT technology, atraditional logistics centre has the ability
to connect devices and units, and manage those units within
anetwork. Fig. 6 shows the connectivity and management
capabilities of IoT in alogistics centre.
Fig. 6. IoT application in logistics centre management [97]
In order to promote intelligent logistics for Industry 4.0,
Lee et al. [98] suggested an IoT-based warehouse management
system with an enhanced data analysis methodology, based on
computational intelligence approaches. Data acquired from
acase rm demonstrated that the suggested IoT-based WMS
might increase warehouse productivity, picking accuracy, and
eciency, while also being resilient to order unpredictability.
e authors also discovered that employing RFID might
increase eciency in order picking by warehouses, pickup
time, and inventory accuracy. Asmart WMS framework was
announced by Hamdy and colleagues [99]. e warehouse
manager could perform more real-time management and
monitoring of the activities because of this solution. e
adoption of WMS and IoT in warehouses was reviewed. e
building components and levels of the IoT were also shown,
carefully.
Öner et al. [100] took acase study into account, for the
application of RFID technology in the wool yarn sector. RFID
is intended for the handling process, including receiving,
picking, and shipping of semi-nished goods, as well as
tracking work-in-progress, inventories, and stock levels. In
order to accomplish this, an architectural framework for an
RFID-based information system for the wool yarn sector
was created and acost-benet analysis was carried out to
determine whether the new system was cost-eective or
not. Additionally, arisk analysis for RFID investments was
performed. In the same study direction, aWMS was created
by Tejesh et al. [101], based on RFID wireless communication
technology. e IoT-based warehouse inventory management
system is designed to track the products t hat are linked to tags
and provide product information and their associated time
stamps for additional verication. Aserver called Raspberry
Pi would monitor and update all data. e entire system
provides an archetype to match the material and information
ow. e website is designed for ease of use and an interface
for the user to track the products in mind. Comparing the
developed system to the already-used warehouse inventory
management systems, it was signicantly more aordable
and operated dynamically.
Alogistics centre’s facilities were connected to acloud
centre, gateways, fog devices, edge devices, and sensors
in Lin et al.’s [102] investigation of the deployment of an
intelligent computing system. is work established an integer
programming model for deploying gateways, fog devices,
and edge devices in their respective potential sites, so that
the total installation cost was minimised under constraints
of maximal demand capacity, maximal latency time,
coverage, and maximal capacity of devices. e locations
of the cloud centres and sensors were determined based on
the factory layout. e system’s deployment was simulated
using amathematical programming model, which chose
the locations of the gateways, fog devices, and edge devices
in the logistics centre, to minimise the overall installation
POLISH MARITIME RESEARCH, No 4/2023 137
cost while maintaining the system’s maximum capacity for
demand, latency, coverage, and device capacity. Two new
paths in the study of the vehicle routing problem (VRP) in
transportation management (under the umbrella of smart
logistics) have emerged, because of intelligent technologies
like IoT and ICT. First, studies on VRP began to focus on
multi-objective models and enhanced intelligent algorithms
for handling dynamic optimisation problems. Data-driven
models and dynamic models with various objectives have
drawn more attention from academics, in terms of model
types, because they address real-time data updating and
coordination amongst numerous transportation agents.
Second, some researchers have shown that the use of Big
Data and geospatial positioning technology enables smart
logistics to perform activities like visualisation, prediction,
control, and decision-making in VRPs [103].
For the purpose of organising fresh integrations of
intelligent food logistics systems, Li et al. [104] presented
alinear approach. e costs of overall production, inventory,
and transportation were minimised, while average food
quality was increased. en, afresh approach was created
to resolve it by fusing the fuzzy logic method with constraint-
based two-stage heuristics. One case study and 185 randomly
generated cases, with up to 100 stores and 12 periods, were
used to evaluate the methodology. e case study’s calculation
results showed that the suggested model and method could
resolve a real situation involving 40 merchants and 7
periods. e authors’ method could give decision-makers
aselection of Pareto solutions and assist them in selecting
apreferred alternative. Moreover, Zhang [105] suggested
apath decision approach based on an intelligent algorithm,
merging the Cyber-Physical System’s characteristics with the
existing logistical system. e equipment layer’s connectivity
architecture and data processing utilised the IoT and cloud
platform data storage technologies, which were based on the
Cyber-Physical System’s logistics path decision model. e
impacts of using ant colony, simulated annealing, and genetic
algorithms on logistic path optimisation were thoroughly
examined. It was determined that the ant colony algorithm
had the best path optimisation impact in solving the logistics
path decision, by comparing the shortest transport route and
convergence rate under the three algorithm decisions.
BIG DATA
Data obtained from the market, such as consumer
preferences and the experiences of logistics users, can be
processed and analysed with the use of big data gathering
technologies, allowing logistics rms to improve the quality
of their services in response to client needs. Additionally,
logistics rms can improve their overall competitiveness by
collecting data about their target markets, such as logistical
costs, basic pricing, and marketplace assets [106][107]. In
order to improve supply chain management and logistics
centre eciency, Big Data analytics sparked arevolution
in inventory monitoring, forecasting, and management. By
analysing massive amounts of data, Big Data provided insights
that would otherwise be impossible to reach, driving the
warehouse closer to its full potential. In the study by Xie et
al. [108], the researchers conducted asurvey of companies,
looking at how Big Data is being used in the management
of logistics, and used logistics hubs as acase study for using
time series models to predict cargo load capacity. e results
showed how smart logistics built on Big Data may improve
logistics in many ways, including eciency, cost, and user
experience. e authors also concluded that the leadership
and making of decisions, customer relationship maintenance,
and resource allocation of logistics rms would all greatly
benet from the judicious use of Big Data technologies.
Wang et al. [109] also conducted research on the topic of
locating logistics facilities through Big Data analysis. is
issue was stated in the form of anonlinear mixed-integer
programme. e simulation analysed the eect of varying
demand, distribution centre operating costs, international
shipping, and client count on the optimal placement of
distribution centres produced in random, massive datasets.
e experimental data showed that the model provided
was practical and stable. is case study demonstrated the
practical use of Big Data in designing adistribution network
by evaluating dierent potential network layouts.
Big data could be espe cially usef ul in inventory management,
as mentioned in the study by Wang et al. [110], where it could
aid the development of cutting-edge inventory optimisation
systems, the forecasting of future inventory requirements,
the meeting of uctuating customer demands, the cutting of
inventory costs, the attainment of amore complete picture of
stock levels, the improvement of inventory ow and storage,
and the reduction of safety stock. Big Data provided additional
information about the logistics hubs that support certain
industries. An advanced data mining strateg y was presented
by Vieira et al. [111], for an automobile sector rm based
on their analysis of proof of concept Big Data in alogistics
centre. Due to the dearth of pre-existing methods, the most
cutting-edge one was employed. To better identify relevant
data to assist decision-making, t he suggested strategy focused
on goals that were user-driven. Another shared objective was
to facilitate communication and consensus during decision-
making. In order to ensure that the proper replacement parts
were available for the right equipment at the right time and in
the right amount, Zheng et al. [112] proposed an intelligent
system for managing inventory that makes use of cutting-
edge technologies, such as the IoT and Big Data Analytics.
e Singapore Economic Development Board anticipated
that this approach would benet the whole of the Singapore
semiconductor sector in the future. e interactions between
providers and consumers should be investigated further to
nd ways to improve openness, adaptability, and satisfaction.
Furthermore, Wahab et al. [113] set out to learn what
variables in Malaysia’s warehousing industry were slowing
down the use of Big Data analytics. The theoretical
underpinning was the TOE model (technology-organisation-
environment). Partial least squares structural equation
modelling was used to evaluate survey responses from 110
logistics rms. e empirica l ndings indicated that the level
POLISH MARITIME RESEARCH, No 4/2023138
of adoption of Big Data analytics was inuenced by relative
advantage, technical infrastructure, absorptive capacity,
and government backing, but that industry rivalry had little
impact on noticeable gains. e results of this research should
make it easier for warehouses to use Big Data analytics in
the most eective ways possible. Big Data analytics are more
likely to be adopted by warehouses that place an emphasis
on operational excellence, ICT infrastructure, and the
integration of new technologies.
e inclusion of Big Data in data collection in the warehouse
is avery feasible option, making data reception more passive.
In addition, the combination of Big Data and IoT is also agood
technological solution for helping the logistics centre become
automated. is was also apremise for conducting transport
ow management outside the logistics centre. e combination
of managing the ow of goods and motor vehicles in and out of
alogistics centre would greatly help in reducing transportation
costs, warehousing costs, and waiting costs.
BLOCKCHAIN
For IoT or Big Data, the application of these technologies in
logistics centres mean exploiting and processing information
to achieve optimal goals, as well as reducing costs. However,
the major drawback of the above applications is their
tra nspa rency, as wel l as the abi lit y to protec t data , and th is is
what blockchain can do. By using examples and frameworks,
Ahmad and colleagues [114] explored how blockchain
technology might revolutionise port logistics and operations.
In addition, researchers designed permissioned architectures
to draw attention to the numerous elements, participants,
and deployment options of port logistics services, in order to
automate these processes. The results showed that blockchain
technology could render it impossible for theft to happen,
with documents linked to data management and storage, eet
management, trade paperwork, as-set and crew approval, and
tracking shipments. This made transactions go more smoothly
and built trust between authorities, organisations, and other
players in the logistics centre transportation environment.
With RFID tags, the supply chain process was described from
the raw materials to the consumer. Each step was recorded in
th e blockch ain to impr ove trans pare ncy, in which th e act ivit ie s
at the logistics centre would be recorded, see Fig. 7.
Fig. 7. e use of blockchain technology inside asupply chain framework [115]
Aparadigm for the combination of blockchain with the IoT
was presented for alogistics centre by Aleksieva et al. [116].
is technology, which made use of smart contacts on the
blockchain, might be used for the logistics of cross-docking
warehouses and shipping. e model showed the ability to
operate eectively when it was possible to classify items in
alogistics centre very well, thereby increasing operational
eciency and reducing waiting times. Blockchain logistics
‘apps’ for the optimum placement of intelligent transport
logistics centres were created by Chen et al. [117], to make
use of the blockchain system’s simplicity and IoT input
devices. is strategy was used to monitor where goods
were in the supply chain at any given time. Based on the
results of the experiments, it was clear that the optimum
location technique is superior to conventional approaches,
in terms of the amount of computing required, the precision
of the locations it produces, the total cost, and the ease with
which warehouse locations might be determined. Applying
an intelligent logistics system built on the IoT and blockchain
technology helps businesses get aclearer picture of their stock
levels and shipping progress in real-time. ereby, it ensures
the assets and capital turnover of the enterprise.
It is impossible not to mention the traceability of
blockchain technology as, with this ability, many applications
have been launched, e.g. product traceability. In order to
reliably record airplane parts and improve traceability
data (with organisation-wide consensus and verication),
Ho and colleagues [118] suggested a blockchain-based
approach that was constructed using Hyperledger Composer
and Hyperledger Fabric. Blockchain was also used to keep
track of inventories at distribution facilities, cutting down
on ineciencies in both time and money. Kurdi et al. [119]
analysed data from a sample size of 303 respondents, using
regression and hypothesis testing with ANOVA, to apply
adescriptive, exploratory, causal, and analytical design. One
particularly noteworthy nding was the eect that blockchain
and smart inventory systems had on the eciency of supply
chains and logistics hubs. Future studies should expand on
the number of sectors and building types studied by using
the same amount of organised research. On the other hand,
Lakshmi et al. [120] used QR codes and blockchain technology
to create a system for trustworthy distribution and open
POLISH MARITIME RESEARCH, No 4/2023 139
inventory management. Distributors, retailers, suppliers, and
manufacturers might all be linked via blockchain technology,
with every transaction between them being permanently
recorded. e use of QR codes helps the ecient management
of this stock. Faster feedback loops mean fewer mistakes in
inventory records and more reliable data for making well-
informed decisions at review intervals.
CLOUD COMPUTING
e term ‘cloud computing’ refers to the delivery of
computing resources and functions through the internet. e
key features of cloud computing include on-demand service
delivery, widespread network access, shared resource pooling,
scalability, and use monitoring and control. Since a large
number of users might share identical assets, cloud-based
platforms automatically monitor and measure the usage of
resources for each user [121]. is allows users to make as little
or as much use of the system’s capabilities as they see t [122].
e most-mentioned advantages of cloud computing is that it
reduces risks in the supply chain and limits the generation of
waste. Supply chain risk might be mitigated and robustness
improved in the same manner as cloud computing in logistics
increases agility (by boosting speed, sca lability, and visibility).
In a poll by Accenture [123], 52% of supply chain executives
claimed that cloud computing has helped them improve
resilience. e executives also claimed a 26% improvement
in the precision of demand projections as a result of using
cloud computing. e eectiveness of supply networks in
reducing waste and their long-term viability are under
increasing examination. is was a major topic of discussion
during COP26, held in Glasgow in 2021. Overall, 48% of
supply chain executives polled by Accenture in 2021 [123]
said that they had reduced waste because of cloud computing.
Companies might use cloud computing to highlight waste
and ineciency in the supply chain and save costs, allowing
them to make adjustments to reduce their waste. e cloud
might assist businesses in reorganising their supply chains to
improve eciency, rene logistics and transport routes, and
maximise resource use, all of which contribute to a smaller
carbon footprint [124]. e application of cloud computing
to each stage in the supply chain was an inevitable trend of
businesses moving towards smar t logistics. In the research by
Jiang [125], the researcher took advantage of cloud computing
to provide a strategy for determining the best geographical
and transitable parameters for an international e-commerce
logistics distribution hub. When micro-inuences were taken
into account, this model performed well. Transportation
distances were stated to be reasonable, ranging from 3.5-7.5
km, when using this approach. Based on this technology,
Zhang [126] also presented a two-layer unloading system for
a railway logistics centre using cloud-edge communication
technology. e simulation ndings demonstrated that the
discharging technique described in this research reduced
the total time cost of unloading by as much as 40%. is
technology’s use also has the potential to expedite inter-
device communication and enhance the ecacy of railway
data transfer. Sharma et al. [127] illustrated research on how
to leverage cloud computing to improve retail warehouse
distribution and supply chain management through
Microso Azure technology. Microso Azure is utilised in
retailing, shipping, and warehousing, as well as supply chain
management. e utilisation of this technology helps cost
savings and eases administration, with more adaptability and
better oversight. ese are just some of the benets of using
this kind of technology in retail centre logistics. Gupta et al.
[128] also conrmed that a suitable application created by
cloud computing may greatly facilitate the simplication and
automation of logistics centre management. Sivakumar et al.
[129] investigated the storage facilities at Chennai Harbour.
e warehouse management system for the Chennai Port
Trust is hosted in the cloud, so that numerous people may
use it from o-site locations. According to the ndings of this
study, warehouse operations benet from cloud computing,
which increases productivity and streamlines the workow.
Furthermore, Barreto et al. [130] noted that electronic contacts
with customers, trade partners, and carriers may be handled
by integrating warehouse administration and transportation
administration using cloud computing technologies.
POLICY IMPLICATION FOR LOGISTICS
CENTRE DEVELOPMENT
Smart logistics centres powered by the IoT, Big Data,
Blockchain, and Cloud Computing would be safer, more
accurate, and more ecient. Additionally, the warehousing
procedure would be expedited, and resources would be util ised
to their fu ll potential. In acentralised warehouse management
system, decentra lised decision-making was possible using IoT.
e hurdles for IoT-based smart warehousing still lie in the
selection of astorage allocation strategy and the optimisation
of indoor routing. e technical limitations of RFID, the IoT’s
limited technological capability, IoT standardisation issues,
IoT data acquisition and processing issues, and IoT security
and privacy concerns, are all obstacles to IoT-based smart
logistics. IoT is unsuitable for sophisticated applications in
logistics due to its constrained computing power and data
processing capabilities. In transportation, IoT has alimited
impact on cargo load optimisation and vehicle selection. IoT
technology is unable to easily tackle the complicated problems
of storage allocation and container/truck loading [131]. IoT
could not be used to achieve the agile WMS [132]. Without
the aid of an intelligent algorithm, IoT technology could not
provide decision-making in truck route optimisation for
the delivery of perishable goods [133]. IoT technology could
gather large amounts of information about delivery resources
and requirements [134][135], but it could not address how to
improve the scheduling and use of delivery resources [20].
It is not sucient to address the issues of resource waste and
excessive cost in last-mile delivery.
Logistics become more dicult during the handling,
palletising, and transporting of custom or limited-edition
products [136]. e occurrence of eventualities modies
POLISH MARITIME RESEARCH, No 4/2023140
the demand for specic products quickly and calls for
adjustments to the warehouse oor plan. Transportation
scheduling changes at short notice also presents another
diculty for traditional logistics. In light of the transit stock
being transported along the supply chain (and its scarcity,
needs, and trends), the issues in current logistics centre on
these factors [137][138], including spikes in the demand
for otherwise stable products [139]. e desire to deploy
Industry 4.0, according to Pereira et al. [140], involves a
variety of technological hurdles with signicant eects on
many aspects of today’s manufacturing industry. erefore,
before implementation begins, it is crucial to dene a plan
for all the actors engaged in the entire value chain and to
come to an agreement on security-related concerns, as well
as the appropriate architecture. Furthermore, a lot of scholars
claim that putting Industry 4.0 into practice is a dicult
task that would probably take ten or more years to complete.
Adopting this new manufacturing method involves several
factors and presents a variety of obstacles and challenges,
including social, political, and economic issues, in addition
to technical, economic, scientic, and energy hurdles. e
gathering, processing, and presentation of manufacturing
process data were three new, demanding activities that
they should be able to test out using specialised Industry
4.0 technology [141]. Industry 4.0 has the potential to bring
about signicant changes in a number of areas that extend
beyond the industrial sector and enable the development
of new business models. With so much rivalry in today’s
market, businesses must constantly adapt to be competitive
in terms of cost, quality, and turnaround time [142]. Due
to global competition, businesses need to be quick to adopt
new technologies and provide new items to the market [143].
Designing productive, ecient, and adaptable techniques is
necessary to ensure process competitiveness throughout the
value chain [142]. e integration of new technologies into
manufacturing processes, goods, and machinery is crucial
to facilitating rapid response to changes in the marketplace
[144]. One of the main obstacles faced by dierent countries
is the lack of policies that allow technology to be applied to
the logistics sector. Fig. 8 illustrates the relationship between
logistics policy and governmental policies. It should be noted
that logistics policy does not have asuperior attitude toward
other policies; rather, it implements some of these (such as
security and transportation policies) and cooperates with
others (e.g. industrial and maritime policies). Nonetheless, it
should be considered in each area of its functioning, including
in macroeconomic and detailed policies and (crucially) it
should not be ‘closed’. is phenomenon is closely related
to the processes of globalisation and aims to create a‘no
barriers’ relationship between regions, states, and continents,
in terms of logistics [145].
Fig. 8. Links between logistics strategy and other industries [145]
e use of 4.0 technology also requires ties with other elds
and sectors within anation. Furthermore, only asmall portion
of 4.0 technology is used in logistics centre management.
Here, the focus is on building anation’s digital infrastructure
and smart infrastructure. Although there are many questions
about 4.0 technology’s ability to safeguard information, its
practical applicability, and the expense of doing so, this is
thought to be one of its most risky. e, or the disclosure of
user-data kept in databases, might compromise user privacy
and impact the customer service of the logistics centre [146].
However, ensuring data privacy is just one of the obstacles
to overcome; lowering operational expenses is also crucial
[147][148]RFID (radio-frequency identification. Many
questions have been raised about whether the application
of these technologies in logistics centres would really cut or
increase costs. As an added argument, applying technologies
in auniform way, or prioritising each technology applied in
logistics centres, would also be atopic for future research.
erefore, in addition to the priority policies aimed at macro-
development for countries, research directions for technology
application should also be explored in future studies of
logistics centres. Developing an acceptable application policy
is aproblem that requires further research.
CONCLUSIONS AND FUTURE PROSPECTS
Exponential growth in the number of products that are
available has led to the persistent challenge of overload within
logistics centres and freight operations in the logistics sector.
Moreover, these activities not only result in the inecient
use of time and resources but also have detrimental eects
on the environment. Hence, the use of novel technology
arises as aviable approach to eectively address these issues
in their entirety. e integration of advanced technologies,
such as Big Data, Blockchain, Internet of ings, and Cloud
Computing (commonly referred to as 4.0 technologies), has
been extensively studied and applied in various domains.
rough previous research and applications, this work
has demonstrated the signicant potential of these 4.0
technologies in enhancing the operational capabilities and
POLISH MARITIME RESEARCH, No 4/2023 141
eciency of logistics centres, particularly in managing and
controlling the movement of goods.
e primary uses of each technology are as follows:
e Internet of ings (IoT) facilitates the collection of
asubstantial volume of data by using RFID tags axed to
individual packages and sensors installed throughout the
whole of the logistics centre. e use of Big Data facilitates
the processing of vast amounts of data in order to provide
assistance for managerial decision-making. Blockchain
technology in the logistics centre provides transparency
across the whole of the workow, including the arrival
and departure of items. Cloud Computing facilitates the
sharing of information while maintaining control, leading to
continuous productivity improvements in logistics centres.
e use of these technologies has the potential to enhance the
intelligence and advancement of alogistics centre. In addition,
it is recommended that future research is directed toward the
development of atechnologically advanced logistics centre
that conforms to established environmental criteria. Hence,
it can be inferred that the adoption of agreen-smart logistics
centre model will become an unavoidable trajectory in the
future. is model would enable the systematic regulation
of goods transportation to eectively cater to the substantial
demand for commodities. Furthermore, these logistics
hubs have the potential to function as seamless extensions
of seaports, therefore mitigating congestion issues in port
cities. Transportation operations within the logistics business
are well acknowledged as being asignicant contributor to
environmental degradation. e escalation of congestion
and prolonged waiting times at conventional logistics
hubs and seaports has led to asignicant rise in pollution
levels, hence posing asubstantial urban challenge. e use
of 4.0 technologies enables the expeditious regulation of
products inside centres, resulting in reduced waiting times
and, subsequently, contributing to the mitigation of vehicle
emissions. Hence, the establishment of agreen and intelligent
logistics centre emerges as aprominent research direction
aimed at mitigating environmental pollution. Simultaneously,
this development aligns with the evolving requirements of
smart cities, which are experiencing rapid global growth.
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