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Metaverse Supply Chain and Operations Management
Alexandre Dolgui1 and Dmitry Ivanov2*
1 IMT Atlantique, LS2N - CNRS, La Chantrerie, 4 rue Alfred Kastler, 44307 Nantes, France
E-Mail: alexandre.dolgui@imt-atlantique.fr
2 Berlin School of Economics and Law
Supply Chain and Operations Management, 10825 Berlin, Germany
Phone: +49 30 308771155; E-Mail: divanov@hwr-berlin.de
* Corresponding author
Abstract
The metaverse and Web 3.0 have created a new digital world with specific properties and be-
haviours replicating and influencing the behaviours and processes of physical entities. This
study aims to advance our understanding of how the metaverse will impact supply chain and
operations management (SCOM). Using elements of a structured literature search and building
on the concepts of cyber-physical systems, digital supply chain twins, cloud supply chains, and
Industry 4.0/Industry 5.0, we propose a framework for metaverse SCOM encompassing multi-
ple socio-technological dimensions. We conclude that further metaverse developments could
result in a co-existence of physical SCOM, metaverse SCOM, and SCOM for coordination of
the physical and metaverse worlds. We offer a structured future research agenda pointing to
new research questions and topics stemming from metaverse-driven visibility, computational
power for data analytics, digital collaboration, and connectivity. New research areas can emerge
for the novel metaverse SCOM processes and decision-making areas (e.g., joint demand fore-
casting for metaverse and physical products, digital inventory allocation in the metaverse, inte-
grated production planning for the metaverse and physical worlds, and pricing and contracting
for digital products), as well as new performance measures (e.g., virtual customer experience
level, availability of digital products, and digital resilience and sustainability).
Keywords: manufacturing; supply chain management; metaverse; digital twin; blockchain; dig-
ital supply chain.
1. Introduction
The metaverse creates a new world where every physical entity (e.g., people, products, and
enterprises) has a digital twin. The entities in the metaverse are not just digital replicas of some
physical entities; rather, they are equipped with artificial intelligence possessing and changing
their own properties and behaviours and even influencing the behaviours and processes of phys-
ical entities. The metaverse is expected to completely change our lives in the very near future,
much faster than we can think of now.
What is the metaverse? The term ‘metaverse’ was coined in 1992 in Neal Stephenson’s literary
work Snow Crash (Stephenson, 1992), where it was visualized as a black spherical planet ac-
cessible to users through terminals with integrated virtual reality capabilities through which
users could appear as avatars (The Economist, 2020). According to Maersk (2022), “[t]he
metaverse is the next evolution of the Internet. It’s a fusing of the digital and physical worlds
powered by technologies, including virtual and augmented reality, blockchain, artificial intelli-
gence, and the Internet of things that connects smart devices”. Moreover, Lovich (2022) defines
the metaverse as “a combination of the virtual reality and mixed reality worlds accessed through
a browser or headset, which allows people to have real time interactions and experiences across
distance.”
The metaverse develops fast. Digital technology leaders like Nvidia with Omniverse and Face-
book with Meta have invested deeply in metaverse solutions (Huynh-The et al., 2023). The
SupplyOn supplier collaboration platform (Holzwarth et al., 2022) and the Catena-X data eco-
system have also been developed in the automotive industry, allowing for the creation of digital
product passports and improving the sustainability and resilience of supply chains from the
perspective of the ecosystem (Catena, 2022). For instance, Siemens and BMW have developed
smart manufacturing platforms using cloud technology (Siemens, 2022; Open Manufacturing,
2022). Furthermore, manufacturing companies like Puma, Nike, Gucci, and Adidas have started
using the idea of the metaverse in marketing and e-commerce to interact with customers, allow-
ing them to view or even buy digital versions of their products (Barrera and Shah, 2023). How-
ever, the role of the metaverse in supply chain and operations management (SCOM) remains
underexplored (Kathiala, 2022).
Mourtzis et al. (2022) claim that the metaverse represents a new era in Internet connectivity,
characterized by interactivity, simulation, a decentralized environment, and persistent reality
facilitated by the next evolution of the Internet (also known as Web 3.0) to combine the digital
and physical worlds. Lee and Kundu (2022) point to conceptual similarities between the
metaverse and cyber-physical systems, the application of which to manufacturing has been dis-
cussed by Panetto et al. (2019). A survey by Accenture (2022a) found that 64% of supply chain
management executives believe that the metaverse will have an impact on their organizations.
Analysis of the existing literature shows that the metaverse’s impacts on SCOM go beyond the
technological dimension: the metaverse is not only a technology but a complex socio-techno-
logical phenomenon. In this setting, a scientific approach is needed to reflect on the chances,
barriers, and challenges that the development of the metaverse will impose on SCOM.
Thus, this study aims to advance our understanding as to how the metaverse will influence
SCOM. In particular we are interested in exploring the following research questions (RQ):
RQ1: How will the metaverse impact SCOM in the physical world?
RQ2: What will be the potential SCOM processes and decision-making areas in the metaverse?
RQ3: What will be the mutual impacts of the co-existence of physical and metaverse SCOM?
We contribute to the literature by proposing a framework describing metaverse SCOM from
multiple socio-technological-economic perspectives, i.e., people, organizations, technology,
management, scope, tasks, and models. We propose that the further metaverse developments
could result in three major decision-making domains in SCOM, i.e., physical supply chains and
operations, metaverse supply chains and operations, and the coordination of physical and
metaverse supply chains and operations. These domains are mutually interconnected.
To provide some guidelines and structure for further research on metaverse SCOM and the
interrelations between physical and metaverse SCOM, we discuss a future research agenda,
namely that future research can explore new opportunities for SCOM that stem from the
metaverse, i.e., visibility, computational power for data analytics, digital collaboration, and
connectivity. At the same time, we show that new SCOM activities can appear specifically
dedicated to the metaverse and lead to novel SCOM processes and decision-making areas (e.g.,
joint demand forecasting for metaverse and physical products, digital inventory allocation in
the metaverse, integrated production planning for the metaverse and physical worlds, and pric-
ing and contracting for digital products), as well as new performance measures (e.g., virtual
customer experience level, availability of digital products, and digital resilience and sustaina-
bility).
The remainder of this paper is organized as follows. In Section 2, the results of a SCOPUS
search for metaverse literature related to SCOM are presented. Drawing upon keyword analysis,
we propose the metaverse SCOM framework in Section 3. In Section 4, future research ques-
tions and new topics that focus on the metaverse are discussed. We conclude in Section 5 by
summarizing the major insights of this study and pointing to some future extensions of them.
2. Analysis of the main topics in the research on the metaverse and SCOM
To understand the state of the art in research on the metaverse and SCOM, we first ran a SCO-
PUS search organised as follows:
TITLE-ABS-KEY ( metaverse ) AND ( LIMIT-TO ( DOCTYPE , “ar” ) ) AND ( LIMIT-
TO ( SUBJAREA , “ENGI” ) OR LIMIT-TO ( SUBJAREA , “BUSI” ) OR LIMIT-TO (
SUBJAREA , “DECI” ) )
We searched for “metaverse” in the titles, abstracts, and keywords of the journal articles in the
business and management, decision sciences, and engineering areas. The search yielded 217
papers and 119 keywords with a minimum threshold of using a particular keyword in at least 3
articles. The result of the VOS Viewer co-occurrence analysis is presented in Fig. 1.
Fig. 1. Metaverse and SCOM research map
Figure 1. Alt Text: Keywords related to the metaverse and SCOM research map
We carefully analysed the keywords identified by SCOPUS and structured them based on the
7-element digital twin framework (Ivanov, 2023b). Accordingly, we propose the following
seven elements to be included in the metaverse SCOM framework: technology, people, man-
agement, organisation, scope, task, and modelling (Table 1).
Table 1. Metaverse SCOM elements
Technology
Organi-
sation
People
Management
Scope
Task
Model-
ling
Virtual Reality
Augmented Reality
Blockchain
Artificial Intelli-
gence
Mixed Reality
3D Computer
Graphics
5G
Industry 4.0
Cloud Computing
Internet of Things
Interactive Com-
puter Graphics
Network Security
Interactive Com-
puter Systems
Cryptocurrency
Remote Control
3D Printers
Cyber Physical
System
Industrial
Metaverse
Real-
Time Sys-
tems
Smart
City
Virtual
Environ-
ments
Decen-
tralization
Virtual
Worlds
E-learning
Extended
Reality
Second
Life
Avatar
Social Net-
working
X Reality
Computer
Aided In-
struction
Human
Computer
Interaction
Streaming
Medium
Decision-
making
Visibility
Sustainability
Performance
Multi Criteria
Decision-
making
Interaction
Web 3.0
Digital
Assets
Digital
Devices
Multi-
media
Con-
tents
Market-
ing
User ex-
perience
Forecast-
ing
Smart
contract
Manufac-
turing
Big Data
Deep
Learning
Machine
Learning
Neural
Networks
Mathe-
matical
Program-
ming
Graphs
Discrete
Events
Systems
Discrete
Events
Simula-
tion
3D Mod-
elling
Digital
Twin
It can be observed in Table 1 that the existing research on the metaverse and SCOM covers a
broad socio-technological-economic spectrum. On the one hand, our analysis allows us to iden-
tify the key digital technologies enabling the metaverse. On the other hand, the key role of
people and the human-machine interface becomes evident through the keywords represented in
Table 1, which was built based on Fig. 1 and supplemented by some additional items based on
our expert review. The metaverse enables new organizational forms and management capabil-
ities (e.g., visibility and interaction). A large variety of artificial intelligence-based modelling
methods supports decision-making tasks in forecasting, manufacturing, and contracting in dif-
ferent system scopes.
3. Metaverse SCOM framework
Based on the keyword analysis, we can now propose a metaverse SCOM framework (Fig. 2).
Fig. 2. The metaverse SCOM framework
Figure 2. Alt Text: Elements of the metaverse and SCOM framework
The metaverse SCOM framework is based on the 7-element digital twin framework proposed
by Ivanov (2023b). The seven major dimensions are people, organization, management, tech-
nology, modelling, scope, and task. In Fig. 2, we combine keywords identified by the SCOPUS
search with our integrative analysis of the relevant frameworks such as digital twins (Negri et
al., 2017; Badakhshan et al., 2022; Berti and Finco, 2022; Burgos and Ivanov, 2021; Frazzon
et al., 2021; Huang et al., 2022), cloud and digital supply chain (Ivanov et al., 2022; MacCarthy
and Ivanov, 2022; Zhang et al., 2022), collaborative networks (Camarinha-Matos and Af-
sarmanesh, 2005), reconfigurable supply chain (Dolgui et al., 2020), cloud manufacturing
(Moghaddam and Nof, 2018), open manufacturing (Kusiak, 2020), Physical Internet (Pan et al.,
2017), and Industry 4.0/Industry 5.0 (Yin and Stecke, 2018; Tang and Veelenturf, 2019; Zen-
naro et al., 2019; Winkelhaus and Grosse, 2020; Choi et al., 2022; Ivanov, 2022a).
Further, in Fig. 3 we illustrate the extension of traditional SCOM understanding as “a cross-
department and cross-enterprise integration and coordination of material, information, and fi-
nancial flows to transform and use the supply chain resources in the most rational way along
the entire value chain, from raw material suppliers to customers” (Ivanov et al., 2021b, p. 9)
towards a triple-SCOM view wherein physical, metaverse, and physical-metaverse SCOMs co-
exist.
Fig. 3. SCOM in the metaverse era
Figure 3. Alt Text: Metaverse, physical, and digital supply chains
Fig. 3 depicts that physical and metaverse worlds are connected through digital technology such
as augmented/virtual reality, blockchain, artificial intelligence, the Internet of things, 5G/Edge
computing, ERP (enterprise resource planning), big data analytics, and simulation (Brintrup et
al., 2020; Cai et al., 2021; Chabanet et al., 2022; Cui et al., 2022; Dolgui and Ivanov, 2022;
Dubey et al., 2021; Elmachtoub and Grigas, 2022). Smart devices and sensors in physical prod-
ucts along with 3D printers represent other data sources for the metaverse. In the metaverse,
digital customers (i.e., avatars) act in the digital markets where digital products are offered and
sold using digital money (probably, a mix of physical and digital products can be considered
too). Managers use digital collaboration spaces for sourcing, production, and logistics coordi-
nation. Also, digital stores, factories, and warehouses represent the supply chain in the
metaverse, which can be digital replicas of physical stores, factories, and warehouses, or repre-
sent new, additional entities which do not exist in the physical supply chain.
4. Open research questions
In this section, we outline open research questions related to the metaverse SCOM.
4.1 Area 1: Scope and task
The scope of the metaverse SCOM will cover digital products, digital factories and warehouses,
the digital supply chain, and digital ecosystems. The metaverse supply chain is not just a digital
replica of a physical supply chain: the digital and physical supply chains evolve autonomously
but co-jointly. When we assume that a digital twin is a digital replica of a physical supply chain,
then the metaverse is more than a digital twin. On the one hand, the metaverse enhances deci-
sion-making support and analytics applications for physical SCOM. On the other hand, the dig-
ital and physical supply chains mutually influence each other (Liu et al., 2020; Lv et al., 2022).
For example, the increased popularity of a product in the metaverse can lead to an increased
demand for this product in the physical supply chain. A timely recognition of these trends
through data analytics can help supply chain managers to prepare for the peak load. The
metaverse data analysis can also be used for the introduction of new products into the market
and decisions on initial order quantity – for example, a product can be first introduced in the
metaverse, and the sales/inventory data from the digital supply chain can be used to set up the
physical supply chain processes. In another example, a product shortage in the physical supply
chain can be substituted by an increased supply of this product in the metaverse so that custom-
ers (or their avatars) who cannot buy the physical product could obtain it in its digital form.
This is a novel context for supply chain resilience management.
Assuming that people will have more and more activities to partake in the metaverse, we can
expect new SCOM activities specifically dedicated to the metaverse and leading to the appear-
ance of novel SCOM processes and decision-making areas. For example, joint demand fore-
casting for metaverse and physical products belongs to a new research area. Since digital prod-
ucts will also require some storage place in the metaverse, digital inventory allocation in the
metaverse can arise as a novel optimization context. Pricing and contracting for digital products
as well as new performance measures (e.g., virtual customer experience level and availability
of digital products, as well as digital resilience and sustainability) can motivate new research.
Through digital analytics, testing and forecasting customer and supplier behaviours can be used
for demand, inventory, and capacity planning. Circular SCOM can receive a new perspective
combining digital and physical reverse flows (Meier et al. 2023).
Inventory management research can also be innovated through the metaverse. For example, one
group of customers might like to have both physical and digital products, another group only
physical, and another only digital – for example, a luxury car, which can be too expensive in
real life can be purchased in the metaverse. Competition between digital and physical products
can lead to interesting new problem settings in pricing and inventory management. In some
cases, digital products can even be wanted more than physical ones – a new setting for revenue
management. Furthermore, sourcing and production planning in the metaverse SCOM can be
adjusted through digital collaboration spaces with improved delivery visibility and coordina-
tion. In addition, physical products might be increasingly supplemented by some digital ser-
vices, and digital products can include some physical add-ons. In this setting, sourcing and
production planning can encounter novel and counter-intuitive decision-making problems.
4.2 Area 2: Management
As indicated in Fig. 2, three SCOMs could exist when the metaverse becomes an important part
of everyday life – SCOM for physical world, SCOM for digital world, and SCOM for coordi-
nating physical and digital worlds. The metaverse can be used for decision-making support in
physical SCOM through enhanced management capabilities such as visibility, computational
power for data analytics, digital collaboration, and connectivity (Dolgui and Ivanov, 2022).
Through supply chain mapping, it becomes possible to obtain more accurate, real-time data on
lead-times, delays, deliveries, shortages, physical locations of containers and trucks, and costs
(MacCarthy et al., 2022). Forecasted known-unknown becomes knowable. For example, in a
metaverse “collaboration room”, supply chain managers could “review expected sales fore-
casts, projected production plans and possible supplier limitations that could affect manufac-
turing volume. They could also see, on an immersive supply chain network map, exactly where
inventory is, virtually walk through key ports to identify possible shipping delays because of
congestion, and model possible alternatives to keep products moving to the right stores and
shelves” (Accenture, 2022b).
Resilience management can be enhanced by disruption recognition, impact prediction, and re-
covery actions (Ralston and Blackhurst, 2020; Ivanov, 2021; Ivanov and Dolgui, 2021; Ivanov,
2022b). Using digital twin-based simulation environments, managers can analyse different sce-
narios in the virtual world using the digital supply chain before implementing decisions in the
physical supply chain. Recognizing bottlenecks and enforcing supply chains for peak loads
(e.g., demand increase) and supply disruptions becomes easier, and stress-testing supply chains
can be performed with higher knowledge awareness (Aldrighetti et al., 2021; Aldrighetti et al.,
2023; Ivanov and Dolgui, 2022a).
Sustainability management can also be improved through transparency about carbon emissions,
visibility about the entire product life cycle, and associated environmental footprints. The dig-
ital supply chain can help in tracing the upstream suppliers to ensure that suppliers do not use
child labour (e.g., by using blockchain or some product-tracking technologies) and produce
products according to sustainability standards and laws.
4.3 Area 3: Technology
Huynh-The et al. (2023) point to six major technological elements of the metaverse, i.e., a dig-
ital twin (cyber-physical interface), neural interface (brain-computer interface), machine vision
(virtual/augmented reality), networking (e.g., multi-access edge computing), blockchain (data
collection, storage, sharing, and management), and natural language processing (e.g., text-to-
speech processing). Bhandal et al. (2022) point to the Internet of things, blockchain, artificial
intelligence and data analytics, augmented and virtual reality, and Industry 4.0 as digital twin
enablers. In addition, through 3D printing, production can be triggered by customers them-
selves. Customers can also design products and have them produced on demand (Boute et al.,
2022; Peron et al., 2022). This will have implications on supply chain complexity and environ-
mental footprints, along with increased customer satisfaction. Finally, digital platforms and
supplier collaboration portals will be used to ensure collaboration and communication in Indus-
try 5.0 (Reim et al., 2022; Holzwarth et al., 2022; Sawik, 2022). End-to-end visibility, which is
so important for both proactive and reactive decision-making, is supported across the supply
chain by ERP systems, blockchain, and T&T systems (Roeck et al., 2020; Choi et al., 2022; Li
et al., 2022; Maccarthy and Ivanov, 2022).
Digital twins can be enabled by technologies of different scopes (Boyes and Watson, 2022;
Nguyen et al., 2022, Jahani et al. 2023). CAD/CAM (computer aided design/computer aided
manufacturing) systems are applied at the product level, while MES and ERP systems enable
the building of the digital twins of processes and organisations. At the supply chain level, spe-
cial software such as anyLogistix in combination with external data sources (e.g., data from
logistics service providers, weather data, financial market data) are used to build supply chain
digital twins (Ivanov and Dolgui, 2021; Burgos and Ivanov, 2021). Future research areas high-
light both a technical understanding of system integration and interoperability and management
conceptualisation of the needs and limits of data-driven decision-making support. Technologies
allow for the integration of models with external data sources and ensure interactions with other
digital twins.
A specific, and very important part of future research on digital twins will be related to human-
artificial intelligence collaboration. According to Ivanov (2023c), three levels of digital twins
can be classified: digital twin, cognitive digital twin, and intelligent digital twin. The latter type
of digital twin is based on human-artificial intelligence collaboration and will therefore be rel-
evant to the metaverse SCOM (Ivanov 2023b).
One particular area of human-artificial intelligence collaboration in the metaverse will be re-
lated to generative AI artificial intelligence (e.g., ChatGPT). Generative AI is expected to have
a profound impact on the physical and digital supply chains taking over (or supporting) a large
variety of SCOM tasks such as demand forecasting, routing optimization, process monitoring,
and risk control. All the activities related to prediction, optimization, and anomaly/failure de-
tection in SCOM will use generative AI.
Finally, cybersecurity issues are of utmost importance for metaverse SCOM. Multiple technol-
ogies and users of the metaverse may lead to increased SCOM cyber threats, resulting in various
new cybersecurity challenges. For example, real-time metaverse SCOM applications may re-
quire new countermeasures against the new cyber threats.
4.4. Area 4: People
The metaverse will change the work and role of people in SCOM. Automatic responses with
minimal human intervention, new standards for working places and remote work, collaboration
of people (virtual meeting platforms), and human-robot collaboration are just some examples
of this change (Rozanek et al., 2022; Sheu and Choi, 2022; Saghafian et al., 2022; Sun et al.,
2022). The metaverse is being developed and used by people, and at the same time it changes
human behaviours and SCOM decision-making.
Decisions in SCOM depend on the expertise of the manager, the knowledge and skills they
exhibit, and their access to real-time data and information (Sgarbossa et al., 2020). The
metaverse can help managers providing decision-making support by acquiring real-time data
and simulating the potential outcomes of certain decisions (e.g., alternative recovery policies
after a disruption or changes in an environmental footprint due to a supply chain redesign).
Digital twins can also consider the level of competence in making decisions (e.g., placing orders
in an inventory control system). Most centrally, the metaverse offers real-time, data-driven de-
cision-making support.
Further research is needed to examine the impacts of continuous access to real-time data on
managerial decision-making. In addition, behavioural aspects of data-driven decision-making
and cognitive biases in human-artificial intelligence interactions belong to the novel topics that
will emerge when digital twins can be explored in SCOM research (Fahimnia et al., 2019; Fu
et al., 2022; Sun et al., 2022). At the manufacturing system level, human-robot collaboration is
one of the central digital twin-related future research topics (Sheu and Choi, 2022). Mourtzis et
al. (2022) stress the human-centric perspective of the metaverse, echoing the integration of hu-
man-centricity, resilience, and sustainability into the Industry 5.0 framework (Ivanov, 2022a).
4.5 Area 5: Organisation
Technology determines organisation. The metaverse will not only mirror physical SCOM or-
ganisations but also create and develop new business and operational models. Through digital
twins, novel organisational constructs such as digital manufacturing, cloud supply chains, and
collaborative platforms will arise (Sharma et al., 2022; Ivanov et al., 2022). Examination of the
metaverse-driven transformations in the organisation of SCOM can be conducted in future re-
search areas where impactful and substantial contributions can be made. In addition, digital
twins can lead to new organisational structures and a redistribution of decision-making compe-
tencies across departments. Metaverse solutions can also be applied to factory design and plan-
ning through simulation of their digital twins. In the created virtual simulation environments,
processes and flows can be represented, analysed, and improved. Furthermore, new organiza-
tional forms (e.g., cloud supply chains, intertwined supply networks, ecosystems) and new cat-
egories in SCOM such as creator economy, discovery, and digital experience could appear too
(Ivanov and Dolgui, 2020).
In the context of viability, digital technology allows for the implementation of the viable supply
chain model (Ruel et al., 2021; Ivanov, 2022a; Ivanov and Keskin, 2023). Visibility, reconfig-
urable manufacturing systems, and additive manufacturing, along with analytics and digital
collaboration tools, are vital for viable manufacturing and supply chains. In light of the increas-
ing resource shortages in physical supply chains due to component (e.g., semiconductors) short-
ages, workforce variability, energy blackouts, and inflation (Ivanov and Dolgui, 2022b; Hägele
et al., 2023), the importance of viable supply chains and the metaverse will continue to grow in
the future.
Following Ivanov (2022a), “the Viable Supply Chain Model is based on adaptable structural
network designs for situational supply-demand allocations and, most importantly, the establish-
ment and control of adaptive mechanisms for transitions between the structural designs”
(Ivanov, 2021e). Moreover, supply chain viability and the ecosystem view have been synthe-
sized through the lens of the human-centred ecosystem perspective by Ivanov and Dolgui
(2022a). In addition, the reconfigurable supply chain framework can be considered a part of
future Industry 5.0 developments (Dolgui et al., 2020; Ivanov, 2023a). Dolgui et al. (2020) note
that by “supplementing the reconfigurable manufacturing concept (Zennaro et al., 2019; Battaïa
et al., 2020), the reconfigurable supply chain adds three specific features: active behaviour of
network elements, networking effects across multiple structures and their dynamics (i.e., or-
ganizational, information, financial, technological, energy), and network complexity (i.e.,
multi-echelon supply chains). The reconfigurable supply chains are characterized by structural
and process variety, which is beneficial for supply chain resilience.”
4.6. Area 6: Modelling
Analytics capabilities offered through the metaverse can hardly be imagined now to a full ex-
tent. Modelling in the metaverse will be based on shifting historical data-based forecasting for
supply chains and operational planning methods towards real time, data-driven decisions (Fig.
4).
Fig. 4. Modelling in the SCOM metaverse framework
Figure 4. Alt Text: Modelling in the metaverse and SCOM framework
Optimisation, discrete-event simulation, neural networks, machine and reinforcement learning,
agent-based modelling, and system dynamics allow for the implementation of the full variety
of descriptive, predictive, and prescriptive algorithms in SCOM (Cavalcante et al., 2019; Rai et
al., 2021; Fu et al., 2022; Kusiak, 2022; Rolf et al., 2022). While real-time data-driven models
constitute a narrow view of digital twins (i.e., a digital twin as a standalone software package),
in a broader sense, digital twins can be considered as a combination of different information
systems and models. Seamless digital and physical integration can become the centric element
of the SCOM metaverse. For example, imagine a product that knows its location, inventory
status, price, and costs. Using edge computing, an algorithm would trigger automatic replen-
ishment, routing, pricing, and demand prediction decisions, thus enhancing margins, product
availability, on-time delivery, and overall profitability. New computational capacities for sup-
ply chain and operations analytics and the use of synthetic data along with the industrial Internet
of things can be used to predict customer and supplier behaviours in terms of demand recogni-
tion and delivery accuracy. Future research can shed more light on the transition from offline
to real-time data-driven modelling, revealing its value and barriers through improved end-to-
end visibility in the supply chain.
5. Conclusion
The metaverse and Web 3.0 represent new and strong triggers for the further evolution of
SCOM. They not only create a new, digital world with specific properties and behaviours rep-
licating the behaviours and processes of physical entities, but also influence physical SCOM.
Despite some fragmented literature that focuses on the metaverse and SCOM, there is a lack of
understanding as to how the metaverse will impact SCOM in the physical world and what the
potential SCOM processes and decision-making areas in the metaverse and the mutual impacts
of the co-existence of physical and metaverse SCOM will be.
Driven by these questions, our study aimed to advance our understanding of how the metaverse
will impact SCOM by drawing on cyber-physical systems, digital twins, cloud and digital sup-
ply chains, and Industry 4.0/Industry 5.0 concepts. With regard to the first research question,
we proposed a framework for metaverse SCOM encompassing seven socio-technological di-
mensions, i.e., organization, management, people, technology, scope, task, and modelling.
Concerning the second research question, our study indicates that new research areas can appear
which are specifically dedicated to the metaverse and novel SCOM processes and decision-
making areas (e.g., joint demand forecasting for metaverse and physical products, digital in-
ventory allocation in the metaverse, integrated production planning for the metaverse and phys-
ical worlds, and pricing and contracting for digital products), as well as new performance
measures (e.g., virtual customer experience level, availability of digital products, and digital
resilience and sustainability).
In answering the third question, our analysis shows that in the future we can expect a co-exist-
ence of physical SCOM, metaverse SCOM, and SCOM for the coordination of the physical and
metaverse worlds. We offered a structured future research agenda pointing to new research
questions and topics stemming from metaverse-driven visibility, computational power for data
analytics, digital collaboration, and connectivity. Further research on digital technology in
SCOM will contribute to the coordination of physical and metaverse supply chains and opera-
tions.
Acknowledgement
The authors thank two anonymous reviewers whose comments helped us enormously in im-
proving the paper.
Data Availability Statement
Data related with this paper is available with authors and will be available upon reasonable
request.
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