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Citation: Mashayekhy, Y.; Babaei, A.;
Yuan, X.-M.; Xue, A. Impact of
Internet of Things (IoT) on Inventory
Management: A Literature Survey.
Logistics 2022,6, 33. https://
doi.org/10.3390/logistics6020033
Academic Editor: Robert Handfield
Received: 30 December 2021
Accepted: 17 May 2022
Published: 26 May 2022
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logistics
Review
Impact of Internet of Things (IoT) on Inventory Management:
A Literature Survey
Yasaman Mashayekhy 1,2,* , Amir Babaei 3, Xue-Ming Yuan 1and Anrong Xue 4
1Singapore Institute of Manufacturing Technology, Agency for Science, Technology, and Research (A*STAR),
Singapore 138634, Singapore; xmyuan@simtech.a-star.edu.sg
2Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad,
Mashhad 9177948974, Iran
3Engineering Faculty, Friedrich-Alexander-University, 91054 Erlangen, Germany; amir.babaei@fau.de
4School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China;
xuear@ujs.edu.cn
*Correspondence: yasaman.mashayekhy@gmail.com
Abstract:
Background: The advancement of Industry 4.0 technologies has affected every aspect of
supply chains. Recently, enterprises have tried to create more value for their businesses by tapping
into these new technologies. Warehouses have been one of the most critical sections in a supply chain
affected by Industry 4.0 technologies. Methods: By recognizing the role of inventory management in
a supply chain and its importance, this paper aims to highlight the impact of IoT technologies on
inventory management in supply chains and conducts a comprehensive study to identify the research
gap of applying IoT to inventory management. The trend and potential opportunities of applying
IoT to inventory management in the Industry 4.0 era are explored by analyzing the literature. Results:
Our findings show that the research on this topic is growing in various industries. A broad range
of journals is paying particular attention to this topic and publishing more articles in this research
direction. Conclusions: Upgrading a supply chain into an integrated supply chain 4.0 is beneficial.
Given the changes in fourth-generation technology compared to previous generations, the approach
of conventional inventory replenishment policies seems not responsive enough to new technologies
and is not able to cope with IoT systems well.
Keywords:
supply chain management; inventory management; Industry 4.0; Internet of Things (IoT);
warehouse management; smart warehouse
1. Introduction
As an essential part of supply chain management (SCM), inventory management is
that it is related not only to manufacturing, but also to pricing. The objective of managing
inventory is to minimize the inventory cost by setting the right inventory replenishment
policies with consideration of various factors to maximize the customer service level.
The very first motivation that caused us to write on this subject was the lack of a
study that gathers all the work previously done on the applications of IoT and Industry
4.0 on inventory management. This study helps to better understand the core concepts
in inventory management and opportunities in the advanced applications of Industry 4.0
in inventory systems and provides solid ground for future works by demonstrating the
current needs and shortages in this particular area.
The scope of the study is limited to three major publishers which had the most
contributions on the subject. We focus on three main keywords in the process of indexing
the pervious works in our paper. This helps us to better focus on a specific domain and
provide quality work on the subject.
This paper is organized as follows. Section 2presents our survey methodology.
Section 3outlines the related studies about the impact of IoT on inventory management.
Logistics 2022,6, 33. https://doi.org/10.3390/logistics6020033 https://www.mdpi.com/journal/logistics
Logistics 2022,6, 33 2 of 19
Section 4analyzes the reviewed papers and presents the findings. Finally, Section 5presents
the conclusion and introduces research gaps and suggestions for further work. You can see
the main contributions of the paper in the Figure 1below.
Logistics 2022, 6, x FOR PEER REVIEW 2 of 19
This paper is organized as follows. Section 2 presents our survey methodology. Sec-
tion 3 outlines the related studies about the impact of IoT on inventory management. Sec-
tion 4 analyzes the reviewed papers and presents the findings. Finally, Section 5 presents
the conclusion and introduces research gaps and suggestions for further work. You can
see the main contributions of the paper in the Figure 1 below.
Figure 1. Main Contributions.
1.1. A Brief on Classical Inventory Models
Inventory, which may contain raw materials, work-in-process (WIP) components, or
finished products, is a significant part of the supply chain. Inventory costs account for a
large percentage of the total supply chain cost. Inventory management aims to optimize
inventory by planning and controlling inventory levels to reduce inventory cost and im-
prove customer service satisfaction. The key research problem is how to answer two fun-
damental questions: “when” and “how many” order should be placed considering supply
lead time, on-hand inventory, etc. To address these two questions, corresponding inven-
tory models must be formulated.
In general, there are two types of inventory review in inventory management based
on the approach to reviewing inventory: periodic review and continuous review. With
continuous inventory review, inventory level must be monitored continuously. An order
should be placed whenever the inventory level is less than a predetermined amount. The
predetermined amount is referred to as the ordering point. The ordering quantity will be
calculated based on the forecasted demand, holding cost, ordering cost, etc. The two sim-
plest classical models with continuous inventory review are the EOQ (economic order
quantity) model and the EPQ (economic production quantity) model. The EOQ model
assumes the ordering quantity is received completely and immediately after ordering,
while the EPQ model assumes the ordering quantity is received incrementally while the
products are being produced.
1.2. Industry 4.0
There are two main streams of view about the Internet of things (IoT) and Industry
4.0 regarding the terminologies and their use. One stream of view considers the terminol-
ogies “Industry 4.0” and “IoT” equivalent and usable interchangeably. Another stream
suggests that IoT is a means of Industry 4.0 and that it can be referred to as an enabler to
the concept of Industry 4.0 [1]. In this paper, we build up our study on the latter view and
look for creative ways that IoT helps in Industry-4.0-related matters.
The idea of the Fourth Industrial Revolution (Industry 4.0) was first introduced by
the German government. It marks a new generation of enhancing organizations’ perfor-
mance with a set of technologies such as Internet of things (IoT), RFID tags, Internet of
service (IoS), cloud computing, big data, cyber-physical systems, etc. The First Industrial
Figure 1. Main Contributions.
1.1. A Brief on Classical Inventory Models
Inventory, which may contain raw materials, work-in-process (WIP) components,
or finished products, is a significant part of the supply chain. Inventory costs account
for a large percentage of the total supply chain cost. Inventory management aims to
optimize inventory by planning and controlling inventory levels to reduce inventory cost
and improve customer service satisfaction. The key research problem is how to answer
two fundamental questions: “when” and “how many” order should be placed considering
supply lead time, on-hand inventory, etc. To address these two questions, corresponding
inventory models must be formulated.
In general, there are two types of inventory review in inventory management based
on the approach to reviewing inventory: periodic review and continuous review. With
continuous inventory review, inventory level must be monitored continuously. An order
should be placed whenever the inventory level is less than a predetermined amount. The
predetermined amount is referred to as the ordering point. The ordering quantity will
be calculated based on the forecasted demand, holding cost, ordering cost, etc. The two
simplest classical models with continuous inventory review are the EOQ (economic order
quantity) model and the EPQ (economic production quantity) model. The EOQ model
assumes the ordering quantity is received completely and immediately after ordering,
while the EPQ model assumes the ordering quantity is received incrementally while the
products are being produced.
1.2. Industry 4.0
There are two main streams of view about the Internet of Things (IoT) and Industry 4.0
regarding the terminologies and their use. One stream of view considers the terminologies
“Industry 4.0” and “IoT” equivalent and usable interchangeably. Another stream suggests
that IoT is a means of Industry 4.0 and that it can be referred to as an enabler to the concept
of Industry 4.0 [
1
]. In this paper, we build up our study on the latter view and look for
creative ways that IoT helps in Industry-4.0-related matters.
The idea of the Fourth Industrial Revolution (Industry 4.0) was first introduced by the
German government. It marks a new generation of enhancing organizations’ performance
with a set of technologies such as Internet of Things (IoT), RFID tags, Internet of service
(IoS), cloud computing, big data, cyber-physical systems, etc. The First Industrial Revo-
lution began with introducing the steam engine to industry. The transition from manual
production to mass production raised new issues and challenges to deal with in industry.
With the spread of electricity use in factories, the Second Industrial Revolution occurred.
Logistics 2022,6, 33 3 of 19
The Third Industry Revolution came with the evolution of the electronic world and the
advancement of information technology (IT). Industry 4.0 has brought new perspectives to
all parts of a supply chain. With Industry 4.0, organizations could reduce waste, increase
responsiveness, and perform real-time decision-making. Cyber-physical systems (CPS)
are natural and human-made systems (physical space) which are tightly integrated with
communication, computation, and control systems (cyberspace). The recent progress in and
extensive implementation of sensors, data acquisition systems, computer networks, and
cloud computing have made cyber-physical systems important infrastructure in various
industry sectors.
On the other hand, the industry’s widespread use of sensors and control systems
has led to a huge volume of data [
2
]. Managing such a huge amount of data (known as
“big data”) needs specific consideration [
3
]. Cloud storage is used for this purpose. By
analyzing demand data and enabling self-decision-making algorithms for the machines in
CPS, the production line can work efficiently with a minimum of direct human role and
fewer errors in real-time interactions. With the use of these new technologies, occupational
psychology becomes important and plays a significant role for the human force. Smart
manufacturing is in place to create automation in an integrated system of CPS, which is will
be more self-guided in dynamic decision-making and interconnection between machines.
The manufacturing section of supply chains has benefited from Industry 4.0, as do
all other sections of the supply chain, such as the distribution section, transportation
section, etc. Industry 4.0 technologies have affected various industries, e.g., aerospace,
agriculture, construction, food and beverages, pharmaceuticals, services, etc. There are
many opportunities available for sustainable manufacturing in the context of Industry 4.0 as
well. The digital cyber network is the key to sharing information in the closed-loop supply
chain to make manufacturing sustainable. Products and processes should be eco-friendly
and take into consideration closed-loop life cycles through re-use and remanufacturing.
To apply Industry 4.0 technologies in practice, organizations require specific infras-
tructures that are able to bring new innovative business models. New business models,
including “disruptive business models”, are needed in a complete digital area to provide
smart goods and services to customers. The idea of the extension of Industry 4.0 would be
realized by automatic virtual metrology, which can reach the zero-defect goal in automation
and extend to Industry 4.1 as the next phase [
4
]. Although the Industry 4.0 concept has
been paid much attention in different fields, the implementation of Industry 4.0 has not
yet been broadly realized in practice successfully [
5
]. Moreover, IoT-based supply chain
systems are not widely studied from academic and industrial perspectives either.
1.2.1. Internet of Things (IoT)
Internet of Things (IoT) was coined by one of the executive directors of the Auto-
ID Center. The idea of network devices has led to the idea that machines could work
dynamically as an integrated system without the interrelated interference of a human
interface which may lead to errors or time wasted. This method of making the machines
smart machines introduces a pictures of manufacturing and production systems, like the
smart factory. The IoT driver receives much attention as one of the Industry 4.0 modules
in this idea. It is a robust communication between the physical and digital world used
in different areas to make goods, operations, and services smarter in the value chain by
offering new potential solutions to alter their functions. Internet-based wireless technology
connects all the devices together for interactions that lead to smarter functions. System
awareness of the environment is also possible via sensors, where devices transmit a large
amount of data in real time. IoT can have a significant effect on the supply chain in the
effective use of resources, transparency and visibility of the entire supply chain, real-time
management of the supply chain, optimizing the supply chain, and increasing agility of the
supply chain [6].
Logistics 2022,6, 33 4 of 19
1.2.2. RFID Technology Enabling IoT
RFID can improve the performance of the whole supply chain from warehousing
to transportation through real-time communication and information sharing. RFID can
improve inventory flow by increasing the traceability and visibility of products. RFID
can help to reduce inventory loss and inventory misplacement and to limit transaction
negligence and supply fault [
7
]. The terminology IoT was used first for defining RFID
tags [
8
]. By connecting RFID readers to an Internet terminal, the items attached with
tags can be identified, tracked, and monitored globally and automatically in real time.
RFID is considered a precondition for IoT. RFID systems refer to a whole that includes
components transmitting data. These components have extensive variety in shapes, models,
and sizes. Their applications are slightly different from one another. However, the two
main components, readers and tags, remain mostly the same. An RFID system may include
one or more readers and tags.
The tags attached to the objects store their unique IDs. The readers send a recon
signal to investigate their surroundings in search of the RFID tags and read their IDs. This
proposes a solution that is useful in logistics, e-health, and security by providing a real-time
map of the objects and therefore transitioning the real world into a virtual representation.
RFID tags are very similar to adhesive stickers from a physical point of view. These tags are
usually passive, meaning that they do not require any power to operate, and are triggered
by using the signal from the readers, which induces power to the tag’s antenna. The power
is then utilized to supply the microchip located in the RFID tag, which will be transmit
the ID stored in it. Conversely, there are two other kinds of RFID which rely on their own
power supplies: semi-passive and active tags. Semi-passive tags use a battery to power
the microchip that stores the ID. Semi-passive tags also use the power transmitted by the
reader to transmit the data. On the contrary, active tags use battery power to transmit the
data to the readers. These two types of readers can provide better coverage but come with
increased costs [9].
1.2.3. IoT Applications
Noting the definition of IoT, its applications are broadly imaginable in many areas
such as safety, security, sustainability, etc. In fact, the applications of IoT technologies are
everywhere around us, such as smart homes, smart cities, self-driven cars, IoT retail shops,
farming, wearables, telehealth care, hospitality, smart supply chain management, etc.
1.3. New Information from Industry 4.0 Brought into Inventory Models
In the past, suppliers had significant effect on production plans. Now, customers
play the main role of defining demands. Thus, production plans should be adjusted
accordingly. Analyzing data to plan production and optimize decisions for competitive
businesses is necessary. Production rates need to be adjusted according to customer demand.
The machines in the production line should work collaboratively based on the received
demand. With change in demand, the production rate should be changed proportionally.
To smoothen the production process, the inventory in the warehouse should be sufficient to
cover continuous demand changes. Therefore, inventory replenishment policies, inventory
review, and ordering quantities should match with changing demand.
By employing Industry 4.0 technologies, specifically IoT, which make devices con-
nected work collaboratively and coordinately, inventory management should be more
responsible for changing inventory operations due to the change in demand. Considering
the smart factory idea in the Industry 4.0 environment and the fact that inventory manage-
ment is the main part of SCM, inventory replenishment policies must be re-reviewed, and
new principles for adapting the Industry 4.0 technologies must be developed [
10
]. As such,
it seems unlikely that conventional approaches could provide the materials in the right
amount with lead time and without shortage for the production or assembly lines. With all
these considerations, we review the available literature on this subject.
Logistics 2022,6, 33 5 of 19
2. Survey Methodology
The paper aims to conduct a holistic literature review about the impact of IoT on
inventory management, identify the research gap of applying IoT to inventory management,
explore the trend and potential opportunities of applying IoT to inventory management,
and suggest future research directions for inventory management. In this study, a content-
analysis-based survey was performed. The articles were collected from three bibliographic
databases: ScienceDirect, Springer, and Emerald.
The keywords were categorized into primary and secondary keywords based on
the articles conceptualized as Industry 4.0 in supply chain management. The primary
keywords used for the initial search are matched to various levels of inventory management
in the supply chain, whereas the secondary keywords reflect one of the most important
technologies in the Industry 4.0 area, IoT, which impacts SCM. Table 1illustrates the
keywords used for our searching.
Table 1. Keywords.
Keywords Details
Primary Keywords
Supply Chain Management (SCM)
Inventory Management
Supply Chain 4.0
Logistics 4.0
Warehouse Management
Secondary Keywords
Industry 4.0
Internet of Things (IoT)
IoT-based Framework
Smart Warehouse
The first search was carried out using the primary search keywords and secondary
keywords that appear in the titles or the abstracts or keywords of the articles. All articles are
written in English, available in online databases of journals and conferences, and published
by scholars and practitioners. With our search range between June 2001 and July 2021, we
faced a limited number of available articles. The subject of this paper is relatively new and
is still under development at the time of penning this paper.
Figure 2shows the steps taken to scan all the retrieved papers. The selection criteria
for our further scanning contain the four steps as follows: (i) Firstly, the collected articles
were reviewed only in titles, keywords, and abstracts. (ii) Six papers were excluded because
of technical problems—for example, because we could not access the full articles. (iii) The
papers irrelevant to inventory management or IoT were excluded. The articles concentrating
on marketing policies or production procedures were omitted because these articles are not
linked exactly to the inventory management part of the supply chain. Moreover, the articles
that only depict electrical devices and the physical-technical methods for implementation
and other scientific issues were eliminated as they are not relevant enough to our literature
review. (iv) Finally, 10 additional articles were added for our references from the three
mentioned databases, plus 2 new papers from two different publishers of all pre-scanned
papers. In total, a sample of 55 articles was reviewed in our study: 42 from Science Direct,
5 from Emerald, 6 from Springer, and 2 from others.
Logistics 2022,6, 33 6 of 19
Logistics 2022, 6, x FOR PEER REVIEW 6 of 19
Figure 2. The systematic survey process.
3. Literature Review
The literature reviewed in the paper can be classified into three categories: initial
preparation of IoT, structural implementation methods and requirements for IoT, and im-
pact of IoT on inventory management in various industries.
3.1. Initial Preparation of IoT
With the advent of Industry 4.0 and its new technologies, the classic approaches in
inventory management have been challenged. New inventory models and approaches
must be innovated to determine inventory replenishment policies with the introduction
of new technology.
Figure 2. The systematic survey process.
3. Literature Review
The literature reviewed in the paper can be classified into three categories: initial
preparation of IoT, structural implementation methods and requirements for IoT, and
impact of IoT on inventory management in various industries.
3.1. Initial Preparation of IoT
With the advent of Industry 4.0 and its new technologies, the classic approaches in
inventory management have been challenged. New inventory models and approaches
must be innovated to determine inventory replenishment policies with the introduction of
new technology.
Ref. [
11
] considered storage agent (SA) actions to reach the optimization goals of
an automated inventory management system. This paper did not apply Industry 4.0
Logistics 2022,6, 33 7 of 19
technologies for the aim of automation planning in this part of supply chain management
(SCM). It compared the Markov decision process (MDP) with other conventional methods
and used the MDP to deal with uncertain problems, including “busy storage place” and
“misplaced product”. Ref. [
12
] proposed using IoT to track the location of components from
a remote location. Doing so can improve the productivity and speed of shipment. It also
provides an accurate status of warehouse stocks and automatically notifies the warehouse
manager. By using RFID tags, intelligent warehouses can control the material flow both
in and out, which leads to proper warehouse scheduling and highly intelligent inventory
management [
13
]. The study by [
14
] suggested that using RFID technology in Inventory
Management can cut down inventory inaccuracy by 20–30% so as to reduce the operation
costs and shortage levels.
Some companies have established special projects targeting warehouse automation
and control through industrial wireless networks (IWN). The study reported IWN ad-
vantages to include reduction of the labor force and increases in mobility and flexibility.
Wireless communication technologies in a warehouse are able to organize thousands of
goods in a specific space. Moxa use RFID and wireless networks to categorize its products
in order to save working time and resources and prevent wire network limitations [
15
].
Each company has its own unique and particular solution for implementing Industry 4.0.
In other words, the solutions and impact of Industry 4.0 would be different between
different companies. Since Industry 4.0 technologies have not been well developed yet,
significant investment and more research in this area must be carried out [16].
Ref. [
17
] introduced the key performance indicators (KPIs) to measure which specific
areas of the supply chain are affected by the technologies of Industry 4.0. The analysis in
the paper showed that order fulfillment is one of the areas which is the most affected by the
introduction of Industry 4.0 through tracking products via IoT and RFID tags. More than
50% of the impact of the new technologies on this part of the supply chain certainly leads
to opportunities, while the rest could be opportunities or threats, depending on the context
of the implication. This ratio of certain opportunities is higher for warehouses—about 67%.
Ref. [
18
] presented online optimization models and showed how they could help cope with
real-time challenges. In practice, a time-dependent model can be of great relevance as it
allows embedding inventory decisions. Ref. [
19
] acknowledged that IoT is able to achieve
collaborative warehousing by using multi-agent systems, which increase the safety and
security of the supply chain. Ref. [
20
] proposed a manufacturing transportation system via
IoT enablers. The system is able to track finished goods and various related items along the
supply chain.
Another usage of IoT in warehouses and inventory management is with the concept of
zero-warehousing smart manufacturing (ZWSM). IoT-enabled infrastructures are required
to achieve a level of visibility that makes the ZWSM concept possible [
21
]. By using IoT, the
smart inventory replenishment system proposed in [
22
] relies on the point of consumption
(POC) data that are gathered from the end customers by extending the vendor-managed
inventory (VMI) to the end customers. Assuming that the manufacturer’s operational
capacity is limited and that customer demand must be fulfilled, the system is designed
to focus on inventory control, customer prioritization, and smart decision-making. The
system showed that inventory replenishment decisions could be improved extensively.
This system can generally enhance the service level and capacity utilization without adding
to the customer’s inventory costs.
3.2. Structural Implementation Methods and Requirements for IoT
The study by [
23
] presented the principle and implementation methods of an auto-
mated warehouse management system (WMS) in a telecommunication company. This
system contains a labeling line in the warehouse and uses Microsoft Visual Studio and
barcodes to show the data of access, location, receiving, and expiry in order to enhance
utility. The study concluded that the performance of the inventory management system
Logistics 2022,6, 33 8 of 19
is improved in terms of the operational cost and accessibility of items. Furthermore, the
system created extra space in the warehouse for the company.
Ref. [
24
] indicated that it is essential to use cloud and fog systems for data storage
and processing in an IoT-based system when designing a smart warehouse monitoring
and control system by using different components such as sensors, network gateways,
actuators, etc. Ref. [
25
] proposed an implementation framework which requires RFID
tags, Wi-Fi module (ESP8266-01), Wi-Fi development board (NodeMcu ESP8266-12e), and
database (Raspberry Pi 3 as the data receiver and web server—programmed with the
Python language).
Ref. [
26
] mentioned that smartphones can be used in industry to scan and record the
data of RFID tags. Doing so would not only save more time, but also enhance inventory
management functions. IoT provides real-time visibility and 100% inventory accuracy. This
study proposed a framework for smart SCM where inventory is dynamically trackable
to managers so that they can connect suppliers and orders in a timely manner via the
integrated system. Ref. [
27
] used a new automatic code acquisition system which replaces
the conventional way that a person has to check the inventory before entering the ERP
system manually to barcode all the entries. Ref. [
28
] considered intelligent shelving and
pallets as the force for driving innovative inventory management in the case of stocking
in warehouses. With this system, tracking and tracing stocks in the warehouse would
become faster, more precise, and safer. Ref. [
16
] presented a model to adopt industry 4.0
in inventory management. An intelligent system is able to measure inventory levels with
an RFID shelf. Thus, it is feasible to control the material flow in a smart warehouse via
mobile devices.
Ref. [
29
] discussed the item delivery problems that may be caused by delivery vehicle
issues or item accumulation in the warehouse. By using IoT, a smart dispatch system
which increases the transparency in the logistics system has been implemented, making
visual management of the distribution system possible. In the study by [
30
], an IoT-based
model for decision making in inventory management, which uses RFID, wireless sensors,
and other middleware technologies at an enterprise level was introduced. Moreover, an
information platform processes the information to ensure that inventory costs remain at
their lowest.
The integration of Industry 4.0 technologies requires the various actors and stakehold-
ers of the supply chain to ensure full collaboration and coordination among all stages of the
value chain [
31
]. By recognizing the impact of integration within the whole supply chain
on warehouse management systems (WMS), transporters will be able to communicate with
the intelligent warehouse management system regarding the location and arrival time to
have it select and prepare a docking slot and arrange the just-in-time and just-in-sequence
delivery. RFID sensors will reveal delivery data simultaneously. They also send the track-
and-trace data to the entire supply chain. WMS can automatically assign storage space
according to the delivery specifications and request the appropriate equipment to move
the goods independently to the appropriate location. When the pallets are moved to the
particular location, the tags will transmit signals to the WMS to provide real-time visibility
of inventory levels, which can prevent extra cost from out-of-stock situations and increase
the management’s ability to make decisions on the settings that might be necessary to
increase customers’ service level.
The study conducted by [
32
] demonstrated the possibility of using a warehouse
equipped with heterogeneous RFID readers from different manufacturers which is not
dependent on a centralized server. Such an implementation could reduce the initial imple-
mentation cost and investment. The real-time analysis of RFID efficiency was incorporated
with indoor localization and navigation of warehouse mobile robots. With RFID and uni-
versal plug and play (UPnP) technologies, [
33
] recommended a new approach to manage
production and logistics processes by turning a product into a smart object, which allows
upgrading the products to intelligent objects and services that result in a high level of
functional interaction. Using the concept of the industrial Internet of Things (IIoT), another
Logistics 2022,6, 33 9 of 19
study mentioned a novel approach to the production of smart products and shaped the
production line in order to minimize energy consumption [
34
]. Ref. [
35
] introduced a
communication system in the supply chain for open communication with its electrical
professional infrastructure and security to benefit from enhancing real-time properties. The
basics of time-sensitive networks (TSN) were explained and compared with the Internet
for this communication system. The communication between Industry 4.0 factories which
are related or working in parallel or in coordination could be improved. Therefore, these
factories can take advantage of the benefits of dynamic inventory aggregation and pooling.
A new model in reducing production time, which affects inventory capacity management,
has been proposed as well. The paper takes an artistic approach by integrating the fuzzy
theory into its model, which results in an optimization in the trade-off between production
time and the costs included [36].
Ref. [
37
] proposed the mechanism that enables objects to communicate via the web
in the warehouse. The mentioned warehouse (full of various objects) is smart and works
with a system that contains RFID sensors and consists of a data collection module and an
administrative module. The paper also simulated and evaluated the proposed system in
various scenarios in the context of discovery time, response time, and transmission failure.
Its effects, as seen in the warehouse, are performance improvement, quick interaction, and
high accuracy. Furthermore, the system was designed and created to be semi-automated.
Therefore, with the absence of the user’s decision-making, it can work properly. This
advantage provides companies more flexibility to shift from their former systems to new
technologies and start using the proposed system easily.
Ref. [
38
] introduced a solution for reverse supply chain management (R-SCM) which is
dependent on a heterogeneous IoT network following digital security controls (DSC) objec-
tives. Inventory management utilizes smart containers, while a LoRaWAN (LoRaWAN
®
is a
LPWAN protocol designed to connect battery operated “things’” to the Internet in regional,
national, or global networks) context network is liable for checking the industrial facilities
by using Bluetooth Low Energy (BLE) and RFID technologies. The four performance tests
used to assess this system were data ingest, geographical spread, data size, and network la-
tency. It was found that the testing results are proper for an inventory management setting.
However, BLE seemed to be the bottleneck for larger arrangements. Ref. [
39
] proposed a
warehouse management method using mobile robots, which are highly automated and
flexible. When a number of such robots operate in the same environment, the challenge
is how to manage them. This can be resolved through a cyber-physical system using IoT,
which leads to finding a collision-free path for these mobile vehicles.
3.3. Impact of IoT on Inventory Management in Various Industries
3.3.1. Spare Parts Manufacturing
Ref. [
40
] proposed a smart inventory management system for two types of spare
parts: consumable and contingent spare parts for a semiconductor manufacturing company.
The system aims to prepare spare parts for the right machine at the right time with the
right quantity through IoT technologies. It would lead to making better decisions and
establishing transparency and flexibility between fabs and suppliers. Ref. [
41
] used IoT
technologies in the aircraft spare parts inventory system to reduce inventory costs and
unavailability risks. Improved fleet management and increased customer stratification were
achieved. There are four types of IoT applications in the airline industry: in-house sourcing,
ad hoc pooling, cooperative pooling, and commercial pooling. The paper reviewed these
four types of applications by using the business model of the KLM Engineering and
Maintenance Department. There are numerous challenges with managing inventories of
maintenance, repair, and operations (MRO) spare parts. Ref. [
42
] applied big data analytics,
machine learning, and IoT to predict maintenance cycles and spare parts needs. MRO spare
part usage in the automotive industry showed the differences in patterns, lead times, and
costs, which need to leverage Industry 4.0 technologies to help improve inventory efficiency.
Logistics 2022,6, 33 10 of 19
3.3.2. Agriculture Products
For precision agriculture in the agriculture industry, IoT can be used to track detailed
information from product production to transportation. It allows stakeholders to receive
real-time information about inventory status. With IoT, cloud technologies can be imple-
mented to support the agriculture supply chain [
43
]. The study by [
44
] on agriculture
logistics suggested RFID-based technology in the agriculture industry. The paper explored
the application of RFID in agricultural production and examined the system’s efficiency.
3.3.3. Food Industry
The paper by [
45
] discussed smart inventory management in the food supply chain
and used the survey and sequential pattern for prediction with the AHP method. The
three factors were presented for measuring the function of the food processing and distri-
bution system on quantity, frequency, and recency (QFR) to indicate the impact of being
smart in the food industry. The study concluded that the system’s performance could be
improved up to 66%. Another IoT application in the food industry is to use an IoT-driven
sustainable food security system in which inventory levels are monitored and tracked
through the whole logistics process, starting from the farm and ending with consumers [
46
].
This can also help policymakers monitor food processing, storage, and delivery to end
consumers while minimizing food losses in the supply chain by controlling temperatures
and planning routines.
Halal food organizations should re-examine their ordinary inventories and influence
new innovations. There are many IoT applications in the Halal Food Store Network
(HFSC) [
47
]. The possibilities and opportunities need to be further explored for the HFSC.
There are five main areas in which the HFSC can benefit: tracking food items, upgrading
supply chain efficiencies, easier livestock management, validation of food’s halal status, and
observing halal accreditations. Ref. [
48
] expressed that for special products such as drugs
and food, which need specific storage conditions, IoT-based alert systems are beneficial and
can lead to more sustainability. Ref. [
49
] proposed a live IoT-based monitoring system for
the food supply chain which shares the information with stakeholders. As an immediate
result, the quality of prepackaged food increases. Another example of smart inventory
systems in the food industry is the IP-enabled soft drink vending machines that benefit
from an inventory system accessible over the internet [
50
]. It is feasible that by using this
technology, one could locate their nearest favorite soft drink in a matter of seconds. This is
one of the earliest applications of the internet in inventory systems, which leads to more
advanced applications of IoT in warehouses.
3.3.4. Pharmaceutical Industry
The study on pharmaceutical supply chains illustrated that using Industry 4.0 technolo-
gies in communication leads to fewer errors in demand forecasting and the improvement
of storage space usage in warehouses [
51
]. RFID can provide expiration date information,
which is the main reason for drug returns, and accurately forecast the reverse flow of
expired and near-expired drugs. Thus, in the reverse flow, which plays a significant role in
pharmaceutical and other perishable product supply chains, information integration is able
to reduce wastage and improve sustainability.
3.3.5. People with Disabilities
Ref. [
52
] introduced an IoT application for people with disabilities. In this study, it
was mentioned that RFID via IoT-based inventory management in stores can help people
with disabilities shop more easily.
3.3.6. Construction Supply Chain (CSC)
The benefits from RFID tracking implementation in construction supply chains were
presented in [
53
]. The material handling process and inventory counting, searching, and
organization in warehouses became more accurate and reliable. In addition to easier mea-
Logistics 2022,6, 33 11 of 19
surable benefits, such as alleviating laborious material handling tasks, shipment reliability
was improved and supply lead time was shortened in the supply chain.
The concrete stocking-related applications of RFID tracking, e.g., counting, searching,
and organizing the inventory, would be most beneficial to the companies with warehouses
of construction materials. By using RFID in warehouses, stock recording and balancing
would be more accurate. Doing so would result in less out-of-stock materials and less excess
stock. Industry 4.0 concepts and technologies have been introduced to the construction
industry differently due to the fact that construction supply chains are usually project-
driven, and their partnerships are temporary and constantly changing. Ref. [
54
] defined
“proximity” as a concept of distance that can affect construction supply chains. Because of
the specific situations at construction sites, delivery lead time and holding cost are the two
major factors influencing the entirety of the construction projects’ performance. Using RFID
can help with tracking and localization and can improve proximity dimensions by solving
the problem of late and early deliveries. Eventually, it can lead to reduced inventory cost,
more efficient on-way inventory, shortened lead time, and fewer damaged goods [55].
Another example of IoT-enabled material inventory at construction sites is the in-
ventory of the construction materials attached with RFID tags. The RFID tags contain
the relevant data of the materials, including the manufacturers, technical specifications,
scheduled installation sites and dates, purchase dates, and more. The RFID system plays
an essential role in material monitoring and control by using IoT at construction sites. Engi-
neers and managers use portable readers to track material delivery, storage, installation
progress, and changes. The data are then transmitted to the dynamic database, which
allows real-time information sharing with other project teams [
56
]. The study by [
57
]
suggested that real-time inventory management can facilitate the construction process. The
suggested method is to use long-range RFID readers in the storage area which can track the
product-specific information stored on the tag attached to the materials. Doing so would
allow the RFID system to read and update the inventory database when the materials
move into or out of storage. This can also help the workers to trace the right materials by
using the tag data. One good example of using IoT in construction supply chain networks
is the use of IoT-enabled devices, augmented reality (AR), and fuzzy-VIKOR-analysis-
based inventory management for the construction projects in the China Pakistan Economic
Corridor (CPEC) [58].
3.3.7. Retailing Industry
The quick response system is an application of IoT in the retailing industry. RFID
facilitates this system by tracking products. It minimizes the backroom inventory and
shelf shrinkage of products while improving store security and ability to analyze sales
data [
59
]. The method of product shelf and sales floor bidirectional movements has been
proposed by incorporating RFID into the model described in [
60
]. This model can account
for misreading from the RFID readers and avoid the disadvantages of fully automatic
inventory control by applying for a simple heuristic extension. An interesting application
is the use of RFID tags in fitting rooms.
An example is a German department store in Essen which uses RFID tags on clothes.
When clothes are brought to the fitting rooms, a smart mirror will show similar items and
suggest complementary clothing choices or accessories based on the information saved
on the tag. This system is used in combination with smart shelves [
59
]. A new model
has been introduced to deliver information regarding supply levels from the retailer to
the manufacturer using RFID tags which increase the accuracy of the orders based on the
retailers’ demand based on machine learning [61].
A challenging issue mentioned in [
62
] is the fact that the inventory data supplied by
the point of sale (POS) are sorted out after the sales are closed. It cannot precisely represent
the data of the products on the shelves. Using RFID-enabled tags and employing a software
agent, an integrated information system is able to overcome the mentioned issue. By being
able to telecommunicate the client inventory level to the manufacturer, the installment of
Logistics 2022,6, 33 12 of 19
an electronic device inside the containers improves the opportunity of just-in-time (JIT)
pickups and reduces the chance of late or unnecessary visits to the client site by 50%, as the
study [
63
] indicated. It can also help the supplier to coordinate shipments and rebalance
the retailers’ stocking positions. A new approach has been mentioned to maximize the
profit of a specific retailer by promoting items that will be expired soon, which helps in
sales, reducing inventory costs, and prevention of the loss of goods [64].
3.4. Companies’ Preparedness for Applying New Technologies
Ref. [
65
] provided a conceptual framework for assessing sustainability in SCM, which
enables companies to understand the preparedness for Industry 4.0 transformation. The
framework contains five enablers—business-based smart operations, technology-based
smart products, management strategy and organization, collaboration, and sustainable
development—with 18 criteria and 62 related attributes. Inventory management was men-
tioned in two criteria of the framework, including IoT and logistics integration. The study
pointed out that concepts such as monitoring, resource management systems, visibility on
in-transit consignment, enabling information-driven decision-making, and location, status
and allocations could be counted as important attitudes of inventory management.
3.5. New Environmental Insights Impact
Greening is the process of transforming usual activities into more environmentally
friendly versions. Integrating environmental insights into supply chain management has
important influences on total environmental and economic improvement, which leads to
more sustainability in the whole supply chain. The study shows that a green IoT system
can improve decision-making in the green supply chain (GSC) and, in the same way, in the
green inventory management to achieve greater sustainability [
66
]. Industry 4.0 capabilities
along the supply chain can affect each of the given dimensions. Such capabilities further
influence the greening of supply chains [
55
]. A new methodology has been introduced
which helps to significantly reduce carbon emissions, which results in an improvement of
the inventory management system [67].
4. Analysis and Discussion
In this section, the findings will be discussed based on the descriptive analytics of the
sample literature we reviewed. The sampling process collects 55 papers for our review.
The distribution of the articles considered for the survey by publication years is illustrated
in Figure 3.
Logistics 2022, 6, x FOR PEER REVIEW 13 of 19
Figure 3. Distribution of the articles reviewed in the study by year.
The majority of papers were published over the last three years. The reason is that
the keywords used by the authors to index the articles were relatively new concepts in the
first decade of the 2000s. Thus, the research gap between the years 2001 and 2010 seems
logical. Figure 4 shows that the interest over time has increased for the above-mentioned
keywords around 2010, which supports the reason behind the unavailability of scientific
work in the first years of the current millennium.
Figure 4. Interest over time for the keyword “IoT”.
Figure 5 shows the increasing interest in this topic over years. In terms of publication
types, 11 out of the 55 considered articles in this study were published in conferences and
44 of them were published in journals, as shown in Figure 4. Table 2 presents the details
of the journals and conferences we surveyed.
1 1 1
3
4
3
1
4
3
7
8
7 7
5
0
1
2
3
4
5
6
7
8
9
2001 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Number of papers published from 2001 to 2021
Figure 3. Distribution of the articles reviewed in the study by year.
Logistics 2022,6, 33 13 of 19
The majority of papers were published over the last three years. The reason is that the
keywords used by the authors to index the articles were relatively new concepts in the first
decade of the 2000s. Thus, the research gap between the years 2001 and 2010 seems logical.
Figure 4shows that the interest over time has increased for the above-mentioned keywords
around 2010, which supports the reason behind the unavailability of scientific work in the
first years of the current millennium.
Logistics 2022, 6, x FOR PEER REVIEW 13 of 19
Figure 3. Distribution of the articles reviewed in the study by year.
The majority of papers were published over the last three years. The reason is that
the keywords used by the authors to index the articles were relatively new concepts in the
first decade of the 2000s. Thus, the research gap between the years 2001 and 2010 seems
logical. Figure 4 shows that the interest over time has increased for the above-mentioned
keywords around 2010, which supports the reason behind the unavailability of scientific
work in the first years of the current millennium.
Figure 4. Interest over time for the keyword “IoT”.
Figure 5 shows the increasing interest in this topic over years. In terms of publication
types, 11 out of the 55 considered articles in this study were published in conferences and
44 of them were published in journals, as shown in Figure 4. Table 2 presents the details
of the journals and conferences we surveyed.
1 1 1
3
4
3
1
4
3
7
8
7 7
5
0
1
2
3
4
5
6
7
8
9
2001 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Number of papers published from 2001 to 2021
Figure 4. Interest over time for the keyword “IoT”.
Figure 5shows the increasing interest in this topic over years. In terms of publication
types, 11 out of the 55 considered articles in this study were published in conferences and
44 of them were published in journals, as shown in Figure 4. Table 2presents the details of
the journals and conferences we surveyed.
Logistics 2022, 6, x FOR PEER REVIEW 14 of 19
Figure 5. Types of articles.
Table 2. Journal and conference distribution.
Type
Title
Number of
Papers
Journal
Advanced Engineering Informatics
2
Alexandria Engineering Journal
2
Annals of Emergency Medicine
1
Automation in Construction Journal
2
Automation in Construction Journal
1
Cluster Computing
1
Computers & Industrial Engineering
1
Computer Communications
2
Computers in Industry
4
Computer Networks
1
Decision Support Systems
1
EURASIP Journal on Wireless Communications and Networking
2
European Journal of Operational Research
1
Expert Systems with Applications
1
Food Control
1
Future Generation Computer Systems
1
Industrial Management & Data Systems
3
International Journal of Advanced Manufacturing Technology
1
International Journal of Advance Research in Computer Science and Man-
agement Studies
1
International Journal of Business Analytics
1
International Journal of Production Economics
1
Internet of Things
1
Journal of Engineering and Technology Management
1
Journal of Network and Computer Applications
1
Journal of Management Science and Engineering
1
Journal of Supercomputing
1
Omega
1
Process Safety and Environmental Protection
1
PSU Research Review
1
Resources, Conservation & Recycling
1
Robotics and Computer-Integrated Manufacturing
1
Sustainable Operations and Computers
1
European Journal of Operational Research
1
80%
20%
TYPE OF ARTICLES
Journal Articles Conference Articles
Figure 5. Types of articles.
Table 2. Journal and conference distribution.
Type Title Number of Papers
Journal
Advanced Engineering Informatics 2
Alexandria Engineering Journal 2
Annals of Emergency Medicine 1
Automation in Construction Journal 2
Automation in Construction Journal 1
Cluster Computing 1
Computers & Industrial Engineering 1
Computer Communications 2
Computers in Industry 4
Computer Networks 1
Decision Support Systems 1
EURASIP Journal on Wireless Communications and Networking 2
Logistics 2022,6, 33 14 of 19
Table 2. Cont.
Type Title Number of Papers
European Journal of Operational Research 1
Expert Systems with Applications 1
Food Control 1
Future Generation Computer Systems 1
Industrial Management & Data Systems 3
International Journal of Advanced Manufacturing Technology 1
International Journal of Advance Research in Computer Science
and Management Studies 1
International Journal of Business Analytics 1
International Journal of Production Economics 1
Internet of Things 1
Journal of Engineering and Technology Management 1
Journal of Network and Computer Applications 1
Journal of Management Science and Engineering 1
Journal of Supercomputing 1
Omega 1
Process Safety and Environmental Protection 1
PSU Research Review 1
Resources, Conservation & Recycling 1
Robotics and Computer-Integrated Manufacturing 1
Sustainable Operations and Computers 1
European Journal of Operational Research 1
Wireless networks 1
Total 44
Number of journals 33
Conference
AASRI Procedia 1
IFAC Conference 5
Procedia CIRP—CIRP Conference
on MANUFACTURING SYSTEMS 1
Procedia Computer Science—Information Technology
and Quantitative Management 1
Procedia Engineering -International Conference on Engineering,
Project, and Production Management Internet 1
Procedia Manufacturing—Manufacturing Engineering Society
International Conference 2
Total 11
Number of conferences 7
Since this is an emerging underexplored field of research, as shown in Figure 5, 38%
of the chosen articles in this study focus on modeling and implementation methodology
and principles. About 15% of the articles were on case studies, which could be investigated
more. The case study articles present a rich vision of complex phenomena and help to
develop theories further.
The percentages in Figure 6indicate the topic is a niche for both practitioners and
academic scholars to apply and improve theoretical methods in inventory management
for different industries since it has not been implemented at an integrated level in most
supply chains. The cross-sectional data collected by either literature review or surveys
constitute 20% of the study. In terms of the conceptual framework, 7% of the articles focus
on presenting the frameworks based on IoT systems. However, some literature reviews
Logistics 2022,6, 33 15 of 19
provide frameworks based on the reviewed papers. The majority of the articles concentrate
on modeling and introducing the platforms, and 20% of the articles contain analytical
concepts and explanations.
Logistics 2022, 6, x FOR PEER REVIEW 15 of 19
Wireless networks
1
Total
44
Number of journals
33
Confer-
ence
AASRI Procedia
1
IFAC Conference
5
Procedia CIRP—CIRP Conference on MANUFACTURING SYSTEMS
1
Procedia Computer Science—Information Technology and Quantitative
Management
1
Procedia Engineering -International Conference on Engineering, Project,
and Production Management Internet
1
Procedia Manufacturing—Manufacturing Engineering Society International
Conference
2
Total
11
Number of conferences
7
Since this is an emerging underexplored field of research, as shown in Figure 5, 38%
of the chosen articles in this study focus on modeling and implementation methodology
and principles. About 15% of the articles were on case studies, which could be investigated
more. The case study articles present a rich vision of complex phenomena and help to
develop theories further.
The percentages in Figure 6 indicate the topic is a niche for both practitioners and
academic scholars to apply and improve theoretical methods in inventory management
for different industries since it has not been implemented at an integrated level in most
supply chains. The cross-sectional data collected by either literature review or surveys
constitute 20% of the study. In terms of the conceptual framework, 7% of the articles focus
on presenting the frameworks based on IoT systems. However, some literature reviews
provide frameworks based on the reviewed papers. The majority of the articles concen-
trate on modeling and introducing the platforms, and 20% of the articles contain analytical
concepts and explanations.
Figure 6. Research methodologies considered in the surveyed articles.
5. Conclusions
In this study, the impact of Industry 4.0 technologies, particularly IoT, on inventory
management was investigated. Upgrading a supply chain into an integrated supply chain
Literature
Review and
Survey
20%
Conceptual
Framework
7%
Modelling
(System &
Platform)
38%
Case Study
15%
Other
20%
DISTRIBUTION OF PAPERS BASED ON RESEARCH
METHODOLOGIES
Figure 6. Research methodologies considered in the surveyed articles.
5. Conclusions
In this study, the impact of Industry 4.0 technologies, particularly IoT, on inventory
management was investigated. Upgrading a supply chain into an integrated supply chain
4.0 is beneficial. Given the changes in fourth-generation technology compared to previous
generations, the approach of conventional inventory replenishment policies seems not
responsive enough to new technologies and is not able to cope with IoT systems well.
From the literature analysis, the trend and potential of IoT opportunities available
in sustainable inventory management space were explored. Our findings show that the
research on this topic is growing in various industries. A broad range of journals is paying
particular attention to this topic and publishing more articles in this research direction. The
systems and platforms that are applying the new technologies to the organizations are the
major parts of this survey. Since each individual company needs its own specific solution
for transformation to a greater high-tech level, this topic is expected to be addressed further
in the future.
6. Research Gaps and Future Work Recommendations
To bridge the research gaps in the literature, the following are suggested.
•
Considering sustainability in inventory management with a focus on the green supply
chain as a whole to achieve more sustainability;
•
Forecasting future customer demand based on data analytics and market intelli-
gence while reviewing the product selling price and customer satisfaction to improve
the accuracy;
•
Reviewing suppliers’ behavior by leveraging the available data and BI to know which
supplier can provide the best quality, price, and response to last-minute orders;
•
Establishing an integrative data-driven inventory optimization model instead of the
conventional sequential approach by leveraging data about suppliers, customers, and
inventory to maximize revenue and customer satisfaction;
•
Using AR-enabled headsets to help workers improve storing and finding items inside
an inventory and for training purposes;
•
Optimization of the placements of items inside a storage facility by applying the results
of data analysis from repetitive orders to minimize labor cost and improve efficiency;
•Improvement on decision making systems and lead-time delivery.
Logistics 2022,6, 33 16 of 19
In Table 3, the application of IoT in inventory management have been classified in
different industries. Based on the literature survey, we propose some future application of
IoT technology in inventory management for the different industries discussed in Section 3.
Table 3. Application of IoT in inventory management in different industries.
Industry Reference
Spare parts [40–42]
Agriculture [43,44]
Food [45–50]
Pharmaceutical [51]
People with disabilities [52]
Construction [53–58]
Retailing [59–64]
Spare parts: For more risk reduction in maintenance operations and inventory of spare
parts, IoT must be connected to cloud computing systems to enable decision support sys-
tems (DSSs) to predict orders of new spare parts based on the current rate of consumption.
Agriculture: Future works can enhance the application of IoT in agriculture product
warehouses by enabling DSSs to indicate the amount and time and the type of the agri-
culture products for farming based on the characteristics of the product, such as volume,
storage conditions, weather conditions, soil quality, and agricultural land. This would lead
to more sustainable agriculture production with minimal waste, optimized use of natural
resources, and less emission.
Food: This industry needs some structured frameworks for food product storage
and transportation and to control and update the condition of vehicle conditions, such as
temperature, humidity, etc. in real time. Additionally, the use of IoT connected to other
Industry 4.0 technologies could help order delivery be more efficient based on capacity and
the vehicle storage conditions needed for transportation.
Pharmaceutical: Improving the lead time of the delivery is one of the concerns that
could be performed more effectively with more progress in use of IoT, especially in emer-
gency situations.
People with disabilities: Establishing and introducing more efficient frameworks of
smart houses and smart cities in practice is needed to meet the demand of people with
disabilities for full use of smart systems.
Construction: One of the problems of construction sites is that inventory control
is more challenging due to the nature of the work because of the lack of dynamically
integrated warehouses. Therefore, future application of IoT sensors and equipment could
upgrade inventory management for this industry by designing and implementing better
sensor systems in the whole construction site, even while working and when the gradual
use of resources takes place in different parts of the site at the same time.
Retailing: The use of smart shelves via IoT could progress to the level that refilling
the shelves would be possible with the help of smart transportation or integration with
robotics in the warehouse.
Author Contributions:
Conceptualization, Y.M. and X.-M.Y.; methodology, Y.M.; validation, A.B.
and A.X.; formal analysis, Y.M.; investigation, X.-M.Y.; resources, Y.M. and A.B.; writing—original
draft preparation, Y.M. and A.B.; writing—review and editing, X.-M.Y. and A.X.; visualization, Y.M.
and A.B.; supervision, X.-M.Y.; project administration, X.-M.Y. All authors have read and agreed to
the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Logistics 2022,6, 33 17 of 19
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
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