sustainability

Article
Towards the Smart Circular Economy Paradigm: A Definition,
Conceptualization, and Research Agenda
Gianmarco Bressanelli 1, * , Federico Adrodegari 1 , Daniela C. A. Pigosso 2 and Vinit Parida 3,4

1 RISE Laboratory, Department of Mechanical and Industrial Engineering, University of Brescia,

25123 Brescia, Italy; federico.adrodegari@unibs.it
2 Section of Engineering Design and Product Development, Department of Mechanical Engineering,
Technical University of Denmark, 2800 Kongens Lyngby, Denmark; danpi@mek.dtu.dk
3 Department of Business Administration, Technology and Social Sciences, Lulea University of Technology,
97187 Lulea, Sweden; vinit.parida@ltu.se
4 Department of Business, History and Social Science, USN School of Business, University of South-Eastern
Norway, 3679 Notodden, Norway
* Correspondence: gianmarco.bressanelli@unibs.it

Abstract: The digital age we live in offers companies many opportunities to jointly advance sus-
tainability and competitiveness. New digital technologies can, in fact, support the incorporation
of circular economy principles into businesses, enabling new business models and facilitating the
redesign of products and value chains. Despite this considerable potential, the convergence between
the circular economy and these technologies is still underinvestigated. By reviewing the literature,
this paper aims to provide a definition and a conceptual framework, which systematize the smart
circular economy paradigm as an industrial system that uses digital technologies during the product
life-cycle phases to implement circular strategies and practices aimed at value creation. Following
this conceptualization, the classical, underlying circular economy principle, ‘waste equals food’, is
reshaped into an equation more fitting for the digital age—that is to say, ‘waste + data = resource’.
Citation: Bressanelli, G.; Adrodegari,
Lastly, this paper provides promising research directions to further develop this field. To advance
F.; Pigosso, D.C.A.; Parida, V. knowledge on the smart circular economy paradigm, researchers and practitioners are advised to:
Towards the Smart Circular Economy (i) develop research from exploratory and descriptive to confirmatory and prescriptive purposes,
Paradigm: A Definition, relying on a wide spectrum of research methodologies; (ii) move the focus from single organizations
Conceptualization, and Research to the entire ecosystem and value chain of stakeholders; (iii) combine different enabling digital
Agenda. Sustainability 2022, 14, 4960. technologies to leverage their synergistic potential; and (iv) assess the environmental impact of digital
https://doi.org/10.3390/su14094960 technologies to prevent potential rebound effects.
Academic Editor: Antonella Petrillo
Keywords: circular economy; digitalization; industry 4.0; literature review; business models; sustainability
Received: 17 February 2022
Accepted: 18 April 2022
Published: 20 April 2022

Publisher’s Note: MDPI stays neutral 1. The Relevance of the Digital Age to the Circular Economy
with regard to jurisdictional claims in The circular economy is recognized by industries, scholars, and policy makers as a
published maps and institutional affil- promising approach to jointly advance the sustainability and competitiveness of value
iations. chains, given its ability to decouple economic growth from resource consumption and waste
generation [1–3]. Moving companies towards the circular economy involves fundamental
changes in industrial ecosystems and a systemic redesign of products, production processes,
business models, value chains, and consumption patterns [4,5]. By doing so, several ‘R’
Copyright: © 2022 by the authors.
strategies (sometimes called R hierarchies or imperatives) may be pursued. For instance,
Licensee MDPI, Basel, Switzerland.
This article is an open access article
the European Council in 2008 issued the Directive 2008/98/EC to define a priority order
distributed under the terms and
and a waste management hierarchy that lays its foundation on the 3Rs [6]. They are reduce
conditions of the Creative Commons (through prevention), reuse, and recycle. Other researchers then proposed a framework
Attribution (CC BY) license (https:// based on the work of Potting et al. [7], grouping several ‘R’ strategies into three categories:
creativecommons.org/licenses/by/ (i) refuse, rethink, and reduce to find smarter manufacturing methods or product usages;
4.0/).

Sustainability 2022, 14, 4960. https://doi.org/10.3390/su14094960 https://www.mdpi.com/journal/sustainability

Sustainability 2022, 14, 4960 2 of 20

(ii) reuse, repair, refurbish, remanufacture, and repurpose to extend product and compo-
nent lifespan; and (iii) recycle and recover to find useful applications for materials [8].
This categorization has been reframed in other scientific articles [9,10]. Other scholars
summarize the divergent perspectives on ‘R’ strategies by proposing 10R typologies [11].
Recently, other authors have proposed limiting the categories of ‘R’ strategies to a 4R
scheme, to make it more comprehensible for managers and companies, based on reduce
(increase material and energy efficiency), reuse products, remanufacture components, and
recycle materials [12].
However, in making the significant transformation towards the circular economy,
several technical, organizational, cultural, and financial challenges arise [13–17]. For
example, products designed to last are unable to respond to fashion and technological
changes. The collection of end-of-use products leads to uncertainties regarding quantity,
quality, time, and place of return, reducing the probability of achieving economic scale
and decreasing the profitability of reuse and remanufacture. In addition, remanufactured
products can cannibalize the sales of existing ones, affecting traditional revenue streams.
Furthermore, regulation, taxation, and policy systems are usually not aligned with the aim
and scope of the circular economy. Low awareness and resistance to change often limit
how the circular economy is embraced, especially given the prevalent linear mindset of
industries and consumers. As a result, the implementation of circular economy projects
requires large investments and often leads to longer and more uncertain payback times
than traditional projects.
Against this backdrop, the digital age offers companies many new opportunities
to overcome these transformational challenges and to jointly advance sustainability and
competitiveness [18]. In fact, digital technologies provide incentives for businesses to imple-
ment circular economy principles by enabling new business models as well as the redesign
of products and value chains to conform to a new smart circular economy paradigm [19–21].
For instance, Michelin implemented the Internet of things (IoT) technology to collect tire-
related data and to enable a tire-as-a-service business model, in which fuel consumption
and downtime are minimized [22]. Groupe SEB leveraged 3D printing to print spare parts
on demand, virtualizing its provision and overall technical assistance processes, thus re-
ducing overstocking, transport needs, and emissions [23]. Walmart tested the IBM Food
Trust blockchain to track the origin, real-time location, and status of food products in its
supply chain network, to prevent food waste and support consumer choice of sustain-
able patterns [24]. Rolls-Royce took advantage of big data collected through the IoT on
jet engine conditions, to improve the design of engines for optimal performance and for
predictive maintenance [25].
Despite these technological projects and their substantial potential, the convergence
between the circular economy and digital technologies is still underinvestigated, and com-
mercial applications in companies remain limited [26,27]. More specifically, the literature
continues to struggle to understand how these technologies might contribute to value
creation in the implementation of the circular economy [28]. A new smart circular economy
paradigm is emerging [20], but the literature still lacks a clear definition and conceptu-
alization of this development as well as an integrative framework on how to approach
the transformation required. Thus, the aim of this paper is to define, conceptualize, and
discuss the smart circular economy paradigm as a new emergent phenomenon. The intent
is to discuss how digital technologies can help to realize the different aspects of the smart
circular economy and to identify promising research directions that will advance research
in this field.
The paper is structured as follows. In Section 2, the research methodology and the
theoretical background are provided. Based on the literature review, a definition and
a framework for the emergent smart circular economy paradigm are conceptualized in
Section 3. Here, the usefulness of the framework is demonstrated by applying the model to
the seven contributions published in the special issue, ‘Circular Economy in The Digital
Age’. Section 4 proposes promising research directions to advance academic discussion
Sustainability 2022, 14, x FOR PEER REVIEW 3 of 19

Sustainability 2022, 14, 4960 3 of 20

Age’. Section 4 proposes promising research directions to advance academic discussion
on how companies can leverage digital technologies in transitioning to the smart circular
economy paradigm. Lastly,
on how companies in Section
can leverage digital5, the study’s conclusions
technologies are presented.
in transitioning to the smart circular
economy paradigm. Lastly, in Section 5, the study’s conclusions are presented.
2. Research Methodology and Theoretical Background
2. Research
2.1. Methodology and Theoretical Background
Research Methodology
2.1. Research Methodology
This paper is centered on a literature review and on developing a conceptual frame-
work. This paper is
To address centered
the researchongap,a literature review
a literature andon
review onthedeveloping
emergence a conceptual
of the smartframe-
cir-
work. To address the research gap, a literature review on the
cular economy paradigm has been carried out, according to the steps representedemergence of the smartin circular
Fig-
ureeconomy
1. Moreparadigm
specifically,has been carried
scientific articles out, according
dealing to the
with the steps represented
intersection in Figure
of the circular econ- 1.
More specifically, scientific articles dealing with the intersection of the
omy and digitalization have been searched on the Scopus database. The keyword ‘circular circular economy and
digitalization have been searched on the Scopus database. The keyword
economy’ has been combined with several terms identifying the digitalization phenome- ‘circular economy’
has such
non, beenascombined with several terms
‘digital technologies’, ‘smart’,identifying the digitalization
and ‘digitalization’. phenomenon,
The search was carried such
outas
in‘digital
Decembertechnologies’, ‘smart’, and
2021 and updated ‘digitalization’.
in March 2022. The The search
search was
string carried out in December
TITLE-ABS-KEY (‘circu-
2021 and updated in March 2022. The search string TITLE-ABS-KEY (‘circular economy’)
lar economy’) AND TITLE-ABS-KEY (‘digital technologies’ OR ‘digitalization’ OR
AND TITLE-ABS-KEY (‘digital technologies’ OR ‘digitalization’ OR ‘smart’) led to the
‘smart’) led to the extraction of 641 documents. A first screening was carried out to exclude
extraction of 641 documents. A first screening was carried out to exclude articles written in
articles written in languages other than English. An important decision was also taken
languages other than English. An important decision was also taken regarding the type of
regarding the type of article: considering the scientific nature of the research, we decided
article: considering the scientific nature of the research, we decided to include only articles
to include only articles published in international, peer-reviewed scientific journals, as a
published in international, peer-reviewed scientific journals, as a measure to ensure the
measure to ensure the quality of the publications selected. As a consequence, conference
quality of the publications selected. As a consequence, conference proceedings and book
proceedings and book chapters were discarded in this step. A total of 402 articles ad-
chapters were discarded in this step. A total of 402 articles advanced to the next step, title
vanced to the next step, title and abstract reading, to determine the eligibility of the arti-
and abstract reading, to determine the eligibility of the articles. Given the objective of the
cles. Given the objective of the research (i.e., to define, describe, and conceptualize the
research (i.e., to define, describe, and conceptualize the smart circular economy paradigm),
smart circular economy paradigm), we decided to focus only on research articles report-
we decided to focus only on research articles reporting a definition and/or a conceptual-
ing a definition
ization and/orcircular
of the smart a conceptualization
economy for the of the smart circularindustry.
manufacturing economyAfterfor the
thismanu-
step, a
facturing industry. After this step, a total of 75 documents remained.
total of 75 documents remained. The same criterion was applied for inclusion during The same criterionthe
was applied
full-text for inclusion
reading step. As aduring
result,the full-text
a final set ofreading step. As
44 documents wasa result,
used asathefinal set for
basis of 44
this
documents wasresults
research. The used as of the
thisbasis for and
analysis this research.
a collectionThe
of results of this analysis and a col-
the definitions/conceptualizations
lection of the definitions/conceptualizations
are provided in Sections 2.2 and 2.3. are provided in Sections 2.2 and 2.3.

Figure 1. Literature Review methodology.

Figure 1. Literature Review methodology.
Building on the previous literature, we provide a definition of the emergent smart
Building
circular on the
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paradigm literature, we provide
a framework comprisinga definition
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of digital is to use the framework
technologies in achievingtosustainability
describe—and prescribe—the
under enabling
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and effects of digital technologies in achieving sustainability under
paradigm. To test the framework and to demonstrate its usefulness, we decided to applythe smart circular
economy
it to theparadigm. To test the framework
seven contributions published in andthetospecial
demonstrate
issue, its usefulness,
‘Circular we decided
Economy in The
toDigital
apply Age’.
it to the seven
Lastly, contributions
based published
on the literature reviewin the
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directions the literature
advance reviewdiscussion
the academic and on the application
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technologies to directions
transition to advance
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economy paradigm
companies
have beencan leverage digital technologies to transition towards the smart circular econ-
drafted.
omy paradigm have been drafted.
Sustainability 2022, 14, 4960 4 of 20

2.2. The Emergence of the Smart Circular Economy Paradigm

Industries are witnessing a digital age as society enters a fourth industrial revolution
(often called industry 4.0 [29]), which is revolutionizing business by capitalizing on digital-
ization, innovation, and collaboration in industrial ecosystems [18]. In this context, and as
discussed later in this paper, digital technologies (e.g., the IoT, big data and advanced ana-
lytics, 3D printing, blockchain, and virtual and augmented reality) can have a direct impact
on the adoption of sustainability practices [30], thus enabling the transition towards a smart
circular economy [31–34]. In fact, digital technologies can enable several functionalities,
from data collection and integration to data analysis and data automation [35]. Nevertheless,
their enabling role is currently fragmented in the scientific literature, and a clear definition
and conceptualization of the smart circular economy paradigm is still lacking [27,34,36].
Previous research attempted to conceptualize the smart circular economy paradigm in
a scattered way (Table 1). Alcayaga et al. conceptualized smart circular systems as indus-
trial systems that are restorative or regenerative by intention and design, where smart use,
maintenance, reuse, remanufacturing, and recycling are included in the business models of
product-service systems, enabled by digital technologies [37]. Kristoffersen et al. conceptu-
alized the smart circular economy as a framework that bonds together data transformation
(from smart products to data, information, knowledge, and wisdom), resource optimization
capabilities (descriptive, diagnostic, discovery, predictive, and prescriptive), and data flow
processes (hierarchical structure of data collection, data integration, and data analysis)
to enable the implementation of circular strategies [20]. To implement a smart circular
economy, organizations should leverage digital business practices on value creation [36].
Dahmani et al. proposed the synergistic combination of lean/eco-design and industry 4.0
to enable a smart circular product design. Their innovative model promoted sustainability
throughout the product life cycle by adopting reduce, reuse, and recycle strategies [38]. On
the other hand, Kayikci et al. emphasized the role of smart circular supply chains, which
would be established by combining the circular economy with smart enablers (including
digital technologies) to provide firms with a competitive advantage. This outcome would
be achieved by managing products effectively, preventing pollution, and supporting the
achievement of the sustainable development goals [39]. Lastly, Lobo et al. defined the
smart circular economy as an industrial system that uses digital technologies to implement
circular strategies such as reduce, reuse, remanufacture, and recycle [40].The studies listed
above make useful contributions to the field, but there is still a lack of clear definition and
conceptualization of the smart circular economy.

Table 1. Previous conceptualizations of the smart circular economy paradigm.

Smart Circular Economy Definition and

Article Year
Conceptualization
Smart circular systems are conceptualized as industrial
systems that are restorative or regenerative by intention and
Towards a framework of smart circular design, where smart use, maintenance, reuse,
2019
systems: An integrative literature review [37] remanufacturing, and recycling are included in
product-service systems’ business models, enabled by
digital technologies.
The smart circular economy is conceptualized in a
The smart circular economy: A digital-enabled
framework that combines data transformation, resource
circular strategies framework for 2020
optimization capabilities, and data flow processes to enable
manufacturing companies [20]
circular strategies.
Smart circular product design is conceptualized as the
Smart circular product design strategies
synergistic combination of lean/eco-design and industry 4.0
towards eco-effective production systems: A 2021
to promote sustainability throughout the product life cycle
lean eco-design industry 4.0 framework [38]
using reduce, reuse, and recycle strategies.
Sustainability 2022, 14, 4960 5 of 20

Table 1. Cont.

Smart Circular Economy Definition and

Article Year
Conceptualization
The establishment of smart circular supply chains is
conceptualized as the combination of the circular economy
Smart circular supply chains to achieving
2021 and smart enablers, to provide firms with a competitive
SDGs for post-pandemic preparedness [39]
advantage by managing products effectively and
preventing pollution.
The smart circular economy is conceptualized as a more
Towards a business analytics capability for the
2021 efficient and effective economy, where organizations
circular economy [36]
leverage digital business practices on value creation.
Barriers to transitioning towards the smart The smart circular economy is defined as an industrial
circular economy: A systematic literature 2022 system that uses digital technologies to implement circular
review [40] strategies such as reduce, reuse, remanufacture, and recycle.

2.3. The Enabling Role of Digital Technologies in the Smart Circular Economy Paradigm
As discussed above, several digital technologies can facilitate the transition towards a
smart circular economy in several ways. We decided to confine our focus to five main digital
technologies (i.e., the IoT, big data and analytics, 3D printing, blockchain, and augmented and
virtual reality) given their relevance and potential for the circular economy [4,30,41]. Their
enabling role in the smart circular economy paradigm is discussed in the following segment.
The IoT, as a technology, describes a network of connected physical objects that are
embedded with sensors (such as radio frequency identification (RFID), printed circuits, or
electronics) [42]. Products embedded with sensors can share information and communicate
with other systems through the Internet. Thus, they become active participants in the
network. The IoT enables a circular economy by facilitating access to the data of products
over their life span (from design and manufacturing to distribution, usage, and end of use)
to support their life-cycle management [26,37]. During manufacturing, the monitoring of
operational data through the IoT expedites the achievement of operational excellence by
reducing scrap rates and equipment wear and tear, with a lower environmental footprint
compared to conventional manufacturing processes [18]. In addition, the IoT enables the
provision of product-as-a-service circular business models (such as sharing or pay per use).
It allows products to become smart, thus facilitating tracking, monitoring for billing pur-
poses, and the provision of full-service contracts, including repair and maintenance [19,43].
Finally, from usage to the end of use, the IoT helps to track product flows, capture product
lifetime information, and minimize the uncertainties involved in recovery strategies—in
particular, with regard to the quality and condition of each product/part/component prior
to disassembly. Consequently, the IoT promotes better managerial decision-making about
alternative circular strategies such as reusing, remanufacturing, and recycling [37].
Big data and analytics are based on extremely large amounts of unstructured data,
which are generated in a continuous stream and are characterized by their large volume,
velocity, and variety. Big data are usually analyzed computationally through data mining
and advanced analytics to identify new information, trends, patterns, and associations. In
this context, artificial intelligence techniques may be employed for both data collection
and data analysis [44]. In fact, big data are commonly used to feed and train machine
learning and deep learning algorithms. Therefore, advanced analytics can be defined
as the ability to transform data into valuable information to increase knowledge [45].
Big data and analytics serve the circular economy through their potential to optimize
processes and enhance decision-making, using the data collected from the IoT to improve
resource management across the entire product life cycle, from manufacturing to end of
use [20,46]. Artificial intelligence can also be an effective tool in helping managers to
identify hidden patterns [47]. For instance, the exploitation of data-driven decision-support
platforms may provide efficient and reliable tools for decision-making in sustainable
Sustainability 2022, 14, 4960 6 of 20

logistics systems [48]. In this context, digital modeling and simulation are used to support
decision-making in several circular economy areas [49]. For instance, big data may provide
valuable information on how customer usage patterns can be used to improve product
design for circularity. Big data and analytics can generate an enhanced understanding of
user behavior and provide useful (and often missing) feedback from the product usage
phase back to design [26,50]. In addition, data mining and advanced statistical analysis
enable the provision of preventive, predictive, and condition-based maintenance [20,51],
including the realization of completely automated workflows where smart and connected
products can predict failures and automatically schedule future maintenance activities [37].
3D printing as an additive manufacturing technique is used to create three-dimensional
objects, layer by layer, starting from a digital computer-aided design (CAD). Products
are manufactured through additive processes—that is to say, the opposite of subtractive
manufacturing processes—where pieces of plastics or metals are cut out by milling, drilling,
and turning machines. Additive manufacturing is a more comprehensive concept than
3D printing, since the former is a broader term encompassing more processes than 3D
printing. In contrast, 3D printing empowers the circular economy by allowing a circular
design to manufacture, repair, reuse, and recycle products [52,53]; 3D printing enables the
circular design of products because recycled materials (plastics and metal powder), instead
of virgin ones, can be used as input in additive manufacturing processes [54,55]. In this
process, the effects of thermal cycles on the mechanical properties of products should be
carefully taken into account because they could impose limits on the reuse of recycled
powder [52]. Moreover, they significantly increase the personalization of products, thus
improving the bond between the customer and the product itself, enhancing emotional
attachment to the products, and averting their early retirement [56]. Regarding circular
manufacturing, 3D printing enables local, on-demand, efficient, and real-time production.
In contrast to conventional subtractive techniques, 3D printing avoids material losses,
scraps, and waste during production, achieving resource efficiency by employing complex
geometries without the need for special equipment [56,57]. Since 3D printing draws on
economies of scope rather than on economies of scale, it reduces the need to maintain a
large inventory [54]. In addition, 3D printing reduces the need for transportation (and its
related economic and environmental impact) because it supports local production through
distributed manufacturing in small-scale plants [54]. Finally, 3D printing enables the
on-demand production of spare parts for repair and upgrading purposes, leading to an
extension of the lifetime of products [58]. In this context, spare parts are stored digitally
and are only produced when a repair is needed, thus reducing inventory size [56].
Blockchain is a system of recording information that draws on a digital, distributed
ledger of transactions. This ledger is stored, shared, and replicated with multiple par-
ticipants across a decentralized network in a way that prevents changing, hacking, or
cheating the system. Some studies have shown how blockchain can potentially increase
firm performance, by adopting circular practices in procurement, design, remanufactur-
ing, and recycling processes [59]. From a practical point of view, blockchain aids the
circular economy in several ways [60,61]. First, blockchain technology ensures trust, trans-
parency, traceability, security, and reliability in the value chain, given its distributed digital
characteristics [62–64]. In fact, all blockchain participants can easily view the ledgers and
analyze transactions, thanks to decentralization. In addition, blockchain incorporates en-
crypted information and consensus mechanisms (proof of work) that reduce the risks of
cyber attacks and system failures [60]. These features allow products to be tracked in the
value chain, including relevant information on their environmental and social conditions
at each stage (such as the materials’ source, the actors involved, the processes carried out,
and the energy consumed) [62]. Thus, blockchain can be used to ensure that purportedly
circular products are environmentally friendly, driving consumer choices and avoiding
greenwashing—namely, the disinformation provided by organizations to present a (false)
environmentally responsible public image. Furthermore, blockchain technology allows
the smart execution of transactions because it connects users without the need for inter-
Sustainability 2022, 14, 4960 7 of 20

mediaries. This is achieved through the execution of smart contracts, leading to greater
efficiency in operational processes [60]. Lastly, blockchain supports—and may facilitate the
design of—incentive mechanisms (e.g., in the form of bitcoin or other cryptocurrencies) to
direct user behavior towards specific actions, such as participation in recycling schemes
(e.g., bitcoins received in exchange for depositing old cans) [47,60,62].
Augmented and virtual reality (AR-VR) are technologies that enable a superior ver-
sion of the real, physical world by adding digital elements to provide an enhanced user
experience [41]. While augmented reality just adds digital elements to a live view, virtual
reality is based on full computer-generated simulations of three-dimensional environments.
Users interact with AR-VR environments through special electronic equipment, such as
smart glasses or gloves equipped with sensors. AR-VR supports the circular economy
thanks to virtualization. In fact, virtualization facilitates the redesign of more repairable
and modular products because of the easier simulation of alternative concepts [20]. In this
context, virtual design and simulation are enabled by generating the so-called digital twin
of a product—that is to say, a virtual representation that works as the digital counterpart of
a physical object [65]. Lastly, AR-VR systems can encourage people to work more flexibly,
providing remote assistance and guidance during service and maintenance activities, thus
reducing transportation needs [42].
Table 2 summarizes the role of digital technologies in the smart circular economy
paradigm on the life-cycle phases of a general product, from design to the end of use.
Sustainability 2022, 14, 4960 8 of 20

Table 2. The role of digital technologies in the smart circular economy paradigm.

Product Life-Cycle Phase

Digital Technology References
Design Manufacturing Distribution Usage End of Use
Monitoring of data to
achieve operational Enabling the provision of circular
Tracking products to
Internet of Things excellence by reducing product-as-a-service business models (pay per [18,19,26,37,42,43]
increase collection rate.
scraps and equipment use, sharing).
wear and tear.
Transforming
Informing better
product-in-use data into Enabling the provision
Big Data and decision-making for
valuable information to of preventive and [19,20,26,37,44,46,47,49–51]
Analytics reuse, remanufacturing,
improve product design predictive maintenance.
and recycling.
for circularity.
Increasing the use of
recycled materials
Minimizing material
(recycled plastic
losses, scraps, and waste Enabling the local and
polymers or
(additive, not Reducing the need for on-demand production
3D Printing metal powders). [54,56–58]
subtractive process). transportation. of spare parts for repair
Increasing product
Reducing the need to and upgrades.
personalization to avoid
hold large inventories.
the early retirement
of products.
Allowing automated Financial incentivization
Ensuring trust, transparency, traceability, security,
transactions (e.g., smart to drive users’
Blockchain and reliability in the value chain to drive green [47,60–63]
contracts), leading to behavior towards
consumer choices and prevent greenwashing.
greater efficiency. increased recycling.
Providing remote
Facilitating the redesign
Augmented and assistance and guidance
of products to [20,41,42,65]
Virtual Reality for maintenance
improve circularity.
activities.
Sustainability 2022, 14, 4960 9 of 20

3. Towards the Smart Circular Economy Paradigm

3.1. Smart Circular Economy: A Definition and Research Framework
Given the scarcity of existing contributions and building on the studies listed in Table 1,
we define the Smart Circular Economy paradigm as:
an industrial system that uses digital technologies during the product life-cycle phases to
implement circular strategies and practices, aiming at value creation through increased
environmental, social, and economic performance.
On the basis of our definition, we propose a framework that consolidates the main
concepts and enables users to organize and classify the existing literature as well as new
contributions, according to the smart circular economy paradigm (Figure 2). The framework
considers five main dimensions, which are affected by the transition towards a smart
circular economy:
1. The underlying digital technologies, such as the Internet of things, big data and
analytics, 3D printing, blockchain, and augmented/virtual reality;
2. The life-cycle phases of a generic product affected by this transformation, ranging
from design to the end of use;
3. The circular economy strategies of reducing, reusing, remanufacturing, and recycling,
according to [12];
4. The circular economy practices—that is to say, the managerial levers that can be
employed to support the implementation of the circular economy in companies
regarding product design, business model, and value chain, according to [4];
5. The targeted creation of value, achievable through an increase in environmental
Sustainability 2022, 14, x FOR PEER REVIEW 9 of 19
performance classified according to the triple bottom-line perspective of economic,
environmental, and social benefits.

Figure 2.
Figure 2. A
A research
research framework
framework for
for the
the smart
smart circular
circulareconomy
economyparadigm.
paradigm.

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In other words, aall the
smart
circular economy makes information work, providing relevant information to the right actor
at the right time, which enables a better utilization of materials. Lastly, the framework
shows that digital technologies are not an end in themselves, but, rather, they are the means
through which the systemic redesign of products, business models, and supply chains are
enabled for the circular economy. Consequently, digitalization for the circular economy is
Sustainability 2022, 14, 4960 10 of 20

life-cycle phases of products to reduce material and energy consumption, reuse products,
remanufacture components, and recycle materials. This, in turn, promotes value creation
and the achievement of enhanced sustainability performance in terms of environmental,
economic, and social benefits.
The underlying principle is that, in a smart circular economy, physical flows should
be progressively replaced by informational flows. The aim is to make a better use of data to
reduce the use of materials, which otherwise would lead to over-production, over-stock,
over-transportation, and over-waste in industrial systems. In other words, a smart circular
economy makes information work, providing relevant information to the right actor at the
right time, which enables a better utilization of materials. Lastly, the framework shows that
digital technologies are not an end in themselves, but, rather, they are the means through
which the systemic redesign of products, business models, and supply chains are enabled
for the circular economy. Consequently, digitalization for the circular economy is much
more than the mere introduction of digital technologies. In fact, digitalization alone will not
automatically lead to better performance and a lower environmental impact. It is, however,
the redesign of products, business models, and supply chains to introduce circular 4R
strategies that will (hopefully) facilitate this, as underscored in the following section.

3.2. Applying the Framework to a Sample of Articles

With the aim of applying the smart circular economy framework to the fresh, new cir-
cular economy literature, we took the seven articles recently published in the Sustainability
special issue, ‘Circular Economy in the Digital Age’, and categorized them according to the
framework (Table 3).
Sustainability 2022, 14, 4960 11 of 20

Table 3. Application of the framework to the seven contributions of the Sustainability special issue ‘Circular Economy in the Digital Age’.

Circular Economy 4R Circular Economy

Article Digital Technology Lifecycle Phase Sustainability Performance
Strategy Practice
Reduce the pace of emissions to a
Green Transition: The
Internet of Things Design Eco-design value lower than the rate at
Frontier of the Digicircular
Big Data and Analytics Manufacturing Reduce New business models based which natural systems can
Economy Evidenced from a
(based on Usage Recycling on servitization absorb them.
Systematic Literature
quantum computing) End of use Value chain reconfiguration Recycle resources at a pace
Review [66]
higher than waste generation.
Reduce the consumption of
natural resources by optimizing
product design based on
digital twins.
Design Product design
Reduce waste generation by
Manufacturing Reuse Servitized business models
Digital Twins for the Circular increasing remanufacturing and
Digital Twins Distribution Remanufacturing (sharing)
Economy [67] recycling, thanks to improved
Usage Recycling Circular value chain
decision-making enabled by
End of Use coordination
digital twins.
Economic benefits from the
optimization of resources during
the product life cycle.
Savings in holding and
transportation costs due to the
Omni-Chanel Network optimization of inventory
Design towards Circular share policies.
Internet of Things Distribution Reduce Value chain optimization
Economy under Inventory Reduce CO2 over-production
Share Policies [68] and transportation emissions due
to the optimization of inventory
share policies.
Circularity for Electric and
Electronic Equipment (EEE), Manufacturing Reduce waste generation,
Remanufacturing
the Edge and Distributed Blockchain Distribution Value chain especially for electrical and
Recycling
Ledger (Edge and DL) End of use electronic equipment (WEEE).
Model [69]
Sustainability 2022, 14, 4960 12 of 20

Table 3. Cont.

Circular Economy 4R Circular Economy

Article Digital Technology Lifecycle Phase Sustainability Performance
Strategy Practice
Regenerate resources (using
Design
Design for green buildings renewable resources).
Internet of Things Manufacturing
Circular Digital Built Reduce (long life, reversibility, Narrow resource flows
Big Data and Analytics (construction and
Environment: An Emerging Reuse improvements in efficiency) (resource efficiency).
3D Printing assembly)
Framework [70] Recycling Circular value chain Slow resource loops (intensify
Blockchain Usage
collaboration usage and extend service life).
End of use
Close the loop.
Prevent electronic
waste generation.
Prevent adverse environmental
and human health effects due to
Using Internet of Things and inappropriate disposal and
Distributed Ledger Reduce recycling of WEEE (e.g., related
Internet of Things Distribution Servitized business models
Technology for Digital Reuse to the illegal exportation of
Blockchain Usage Value chain management
Circular Economy Remanufacturing e-waste to developing countries
Big Data and Analytics End of use coordination
Enablement: The Case of Recycling that use child labor and whose
Electronic Equipment [71] dismantling practices create
hazardous pollution).
Increase compliance with
legislative requirements, such as
the WEEE directive.
Industry 4.0 and Smart Data Reduce the environmental
as Enablers of the Circular Design impact of the product (ceramic
Internet of Things
Economy in Manufacturing: Manufacturing Reduce Eco-design tiles), thanks to eco-design
Big Data and Analytics
Product Re-engineering with Distribution informed by the IoT and Big
Circular Eco-design [72] Data Analytics.
Sustainability 2022, 14, 4960 13 of 20

The paper by De Felice and Petrillo [66] investigated how digital technologies can sup-
port a circular economy, identifying the current state of the art and defining future research
developments in this field. They investigated: (i) the role of the IoT as well as big data and
analytics (based on quantum computing) in implementing product eco-design, (ii) new
business models based on servitization and supply chain reconfiguration to improve the
use of natural resources, (iii) reduction in the pace of emissions to a value lower than the
rate at which natural systems can absorb them, and (iv) the recycling of resources at a pace
higher than waste generation. The paper by Preut, Kopka, and Clausen [67] presented
the potential contributions of digital twins to the management of circular supply chains
and the circularity of resources. They investigated how digital twins can be employed
to design products and share business models, and to coordinate a circular supply chain
across the life-cycle stages of manufacturing, distribution, usage, and end of use. In this
way, digital twins can reduce the consumption of natural resources by optimizing product
design, and they can lessen waste generation by increasing remanufacturing and recy-
cling as a result of improved decision-making. The paper by Izmirli, Ekren, Kumar, and
Pongsakornrungsilp [68] studied different lateral inventory share policies in a digitalized
omni-channel supply chain, in which each network shares real-time inventory data and
demand information with each other, enabled by the IoT. In this work, the authors stressed
how supply chain optimization, employing the IoT in logistics and distribution processes,
helps to achieve savings in holding and transportation costs and, at the same time, re-
duce CO2 over-production and transportation emissions (from optimizing inventory share
policies). The paper by Andersen and Jæger [69] investigated how manufacturers of elec-
trical and electronic equipment can build on extended producer responsibility to increase
the circularity of products. They explained how the adoption of blockchain in supply
chains can increase remanufacturing and recycling to reduce waste generation, especially
in electrical and electronic equipment. The paper by Çetin, De Wolf, and Bocken [70]
examined which digital technologies have the potential to expand the circular economy
into the built environment, exploring different methods and implementation paths. More
specifically, several digital technologies (the IoT, big data and analytics, 3D printing, and
blockchain) can be employed to enable circular supply chain coordination and design for
green building practices, such as long life, reversibility, and improvements in building
efficiency. In this way, it is possible to achieve sustainability performances by regenerating
resources (e.g., using renewable resources) and by narrowing, slowing, and closing re-
sources loops. The study by Magrini, Nicolas, Berg, Bellini, Paolini, Vincenti, Campadello,
and Bonoli [71] discussed the application of the IoT and distributed ledger technologies
based on blockchain in the context of enabling different circular economy strategies for
the professional electronic equipment industry. Using a case study of five Italian compa-
nies in the electronics supply chain, the authors explained the enabling role of the IoT,
blockchain, and big data and analytics in implementing servitized business models and in
providing better coordination of the overall supply chain during distribution, usage, and
end-of-use processes. Results vary from the prevention of electronic waste generation to
the prevention of adverse environmental and human health effects from the inappropriate
disposal and recycling of WEEE (e.g., from the illegal exportation of e-waste to developing
countries that use child labor and whose dismantling practices cause hazardous pollution).
In addition, an increase in compliance with legislative requirements, such as the WEEE
directive, is registered. Lastly, the research by Vacchi, Siligardi, Cedillo-Gonzalez, Ferrari,
and Settembre-Blundo [72] developed and applied eco-design principles based on the
integration of the IoT, big data, life cycle assessment, and material microstructural analysis
in the Italian ceramic tile manufacturing industry. More specifically, eco-design practices
were enabled by the IoT as well as big data and analytics to reduce the environmental
impact of the ceramic tile product.
Sustainability 2022, 14, 4960 14 of 20

4. A Research Agenda for the Smart Circular Economy Paradigm

Although existing studies have provided relevant contributions to the literature,
they have failed to encompass the full range of research perspectives in the domain of
the smart circular economy paradigm. Therefore, several areas remain open for further
research. We have identified four research directions, which constitute promising avenues
for future research.

4.1. Develop the Research Objectives and Methodologies from Exploratory to Confirmatory
Purposes, and from Descriptive to Prescriptive Frameworks (Research Perspective)
The current literature has largely limited itself to exploring the potential of digital
technologies for the circular economy, through literature reviews and single case studies.
However, significant movement towards a mature theory on the smart circular econ-
omy paradigm will require the development of research objectives and methodologies to
generate hypotheses and constructs for such a theory, and to statistically test them with
quantitative methods. Future research should, thus, focus on models and frameworks that
support prescriptive decision-making activities, relying on a variety of research objectives
and methods. See, for instance, the work of Di Maria et al. [28], who investigated the
mediating role of supply chain integration at the nexus of industry 4.0 and the circular
economy using a quantitative regression model, or the work of Nayal et al. [73], who
investigated the relationships between digital technology adoption, the circular economy,
and firm performance by using structural equation modelling.

4.2. Move the Focus from Single Organizations to the Entire Ecosystem of Stakeholders (Business
Strategy and Organizational Perspective)
Research on the topic of the smart circular economy paradigm should not be confined
to advancements in technological fields. Instead, innovation should be related to the inno-
vation of organizational and business models paradigms, aligned with the proposed move
towards industry 5.0, with the focus on human progress and well-being [74]. However,
current research often takes a single firm-centric view rather than an ecosystem perspective
involving the full spectrum of stakeholders participating in a circular value chain. There-
fore, new research should move away from the confines of single organizations and extend
the research scope to the entire network of actors. This enlargement should extend to the
global level because no organization or nation is sovereign when it comes to the circular
economy and sustainability. Digital technologies have been proven to be a strong enabler
of connection and cooperation in circular value chains in diverse markets. This may call for
the intra-organizational revision of roles and responsibilities between the customer-facing
‘front end’ and the headquarters-based ‘back end’. Nevertheless, information managed
through digital technologies is rarely shared along the value chain, principally because
of issues concerning the disclosure of sensitive information, data security, and data pro-
tection. Future research should, therefore, focus on defining incentives (e.g., financial)
and requirements (e.g., legislative) to encourage cooperation and information sharing in
circular value chains. Digital technologies have the potential to enable the transition to the
circular economy in entire industrial ecosystems, but the path towards achieving circularity
differs a lot depending on the involvement of a supply chain led by circular economy native
companies (e.g., start-ups specifically born to seize Circular Economy opportunities) rather
than circular economy adopters (e.g., large multinationals pushed to embrace Circular
Economy by external pressures). See, in this regard, the work of Bressanelli et al. [58].
Thus, a promising avenue for future research is to deepen the different circular-economy-
enabling roles of digital technologies for both native companies and adopters, highlighting
differences and similarities. Moreover, we encourage future studies to look closely into
the digital technology adoption process in different contexts. For example, the adoption
process will vary between larger firms and SMEs, as it depends on different industrial
contexts (see, for instance, the work of Chaudhuri et al. [53]).
Sustainability 2022, 14, 4960 15 of 20

4.3. Combine Different Enabling Digital Technologies and Study Their Interlinked Effects on the
Circular Economy (Technology Perspective)
The previous literature investigated only a few digital technologies at a time, perhaps
focusing on one or a limited set. However, most digital technologies should interact
with each other to perform circular economy tasks. Therefore, future research should
provide a more comprehensive picture of the combined role and impact of different digital
technologies in the circular economy, leveraging the synergistic potential of the IoT, big
data and analytics, 3D printing, blockchain, AR-VR, and so forth. In addition to studying
the effects of their combined enabling role, researchers are called to further address the
practical lack of interoperable solutions and communication protocols, which hinders the
integration of heterogeneous systems. Thus, new research should focus on the development
of common standards and communication protocols that allow for the integration of
different technologies. The combination of different technologies should also advance the
debate between edge computing and cloud computing. In fact, the IoT normally operates
at the edge of the network, while data sharing usually occurs through the cloud. Big data
analytics is sometimes carried out at the edge; at other times, it is executed in the cloud.
New research should, therefore, focus on highlighting which operations are best executed
at the edge and which operations should be performed in the cloud, weighing the pros and
cons of each (vertical or hybrid) architecture.

4.4. Assess the Environmental Impact of Digital Technologies on the Circular Economy to Show
That Environmental Gains Offset Their Intrinsic Environmental Cost (Assessment Perspective)
Previous research has mainly focused on highlighting the potential benefits associated
with the introduction of digital technologies to achieve a circular economy. This paper is
no exception. However, digital technologies come at a cost to the environment in terms
of resource depletion (we rely on raw materials to produce their hardware, and these
materials are often critical in terms of availability and supply), energy consumption (digital
technologies need energy to function, which is largely produced from fossil fuels), and
waste generation (the hardware connected to digital technologies is usually dumped in
landfill, and its reuse, remanufacturing, and recycling rates are still low worldwide). For
instance, a common sustainability tension in blockchain is its very energy-intensive op-
eration. The same holds for data centers behind the IoT as well as big data and analytics
activities. The belief that the circular economy results achieved through digital technolo-
gies will offset their intrinsic environmental costs is yet to be investigated (and proven).
Therefore, future research should deepen our understanding of the environmental impact
of digital technologies—see, for instance, Obringer et al. [75]—in relation to the potential
benefits achieved through the circular economy by analyzing, quantifying, and comparing
environmental gains and pains using life cycle assessment to consider potential trade-offs
and rebound effects connected to the implementation of such digital technologies [76].
Thus, we encourage future studies to closely examine how digitalization provides a higher
degree of transparency through the sharing of data across organizations, leading to the
communication of sustainability performance and benefits.
The research directions are summarized in Table 4.
Sustainability 2022, 14, 4960 16 of 20

Table 4. A research agenda for advancing the smart circular economy paradigm.

Research Direction Perspective Highly Promising Avenues

1.1 Develop research objectives and
methodologies to generate hypotheses
and constructs of the smart circular
economy theory and statistically
§1 Develop the research objectives and
test them.
methodologies from exploratory to
Research objectives and methodologies 1.2 Develop models and frameworks to
confirmatory purposes, and from descriptive
support prescriptive
to prescriptive frameworks.
decision-making activities.
1.3 Rely on a variety of research objectives
and methods.
2.1 Shift away from the confines of single
organizations, extending the research
scope to the entire network of actors.
2.2 Focus on defining incentives (e.g.,
financial ones) and requirements (e.g.,
legislative ones) to encourage
§2 Move the focus from single organizations to cooperation and information sharing in
Business strategy and organization
the entire ecosystem of stakeholders. circular value chains.
2.3 Deepen the different
circular-economy-enabling roles of
digital technologies for both native
companies and adopters, highlighting
differences and similarities.
3.1 Provide a more comprehensive picture
of the combined role of different digital
technologies in the circular economy,
leveraging their synergistic potential.
3.2 Address the practical lack of
interoperable solutions and
communication protocols through the
§3 Combine different enabling digital
development of common standards and
technologies and study their interlinked effects Technology
communication protocols.
on the circular economy
3.3 Advance the debate between edge
computing and cloud computing,
highlighting which operations should be
executed at the edge and which
operations should be carried out in the
cloud architecture.
4.1 Deepen knowledge on the
environmental impact of digital
technologies in relation to the potential
benefits achieved through the circular
economy by analyzing, quantifying, and
comparing environmental gains and
§4 Assess the environmental impact of digital pains through life cycle assessment, so
technologies on the circular economy to show as to consider potential trade-offs and
Assessment and evaluation
that environmental gains offset their intrinsic rebound effects connected to the
environmental cost. implementation of such digital
technologies.
4.2 Explain how digital technologies can be
used to provide transparency about
sustainability benefits across a
value chain.

5. Conclusions
By reviewing the literature and by making use of conceptual development, this pa-
per provides a systemic understanding of the broad topic of the smart circular economy
paradigm. The framework clearly shows that digitalization is not primarily associated
with the adoption of some specific technology but is rather built on a combination of
different techniques. The framework also shows that digital technologies are not an end
in themselves, but, rather, they are the means through which the systemic redesign of
products, business models, and supply chains are enabled for the circular economy. This
Sustainability 2022, 14, 4960 17 of 20

conceptualization takes the view that digitalization for the smart circular economy is much
more than the mere introduction of digital technologies, and that digitalization alone will
not automatically lead to a higher sustainability performance. We, therefore, propose to
adapt the underlying principle of the classical circular economy, ‘waste equals food’, to an
equation more fitted to the digital age we are living in, namely:

waste + data = resource

In other words, the disruptive potential of digital technologies should be unleashed

to turn waste into a resource, leveraging data as an essential raw material from which
information and knowledge can be derived to generate sustainable value [77]. Finally, we
sought to provide promising research directions to advance research on the smart circular
economy paradigm (see Table 4) regarding the need to: (i) develop the research objectives
from exploratory and descriptive to confirmatory and prescriptive purposes, relying on a
wide spectrum of research methodologies; (ii) move the focus from single organizations to
the entire ecosystem of stakeholders; (iii) combine different enabling digital technologies;
and (iv) assess the environmental impact of digital technologies to prevent rebound effects.
These research directions will help future researchers to sharpen the academic focus and
avoid saturating research in the field of the smart circular economy.
This work carries certain managerial implications. It provides decision-makers with
a framework that illustrates the relations between digital technologies, product life-cycle
phases, circular strategies, circular economy practices, and potential benefits. Besides being
a useful way to organize and map existing studies (as shown in Section 3), the framework
can support managers in the analysis and categorization of potential smart circular economy
projects. In particular, the proposed framework provides a conceptual structure on how
to move towards a smart circular economy. It can, therefore, act as a powerful guide
delineating the state of the art of a portfolio of smart circular economy projects, and
what needs to be further developed. When putting the smart circular economy paradigm
into practice, it might be useful for managers and policymakers alike to understand all
the possible interrelations among digital technologies, circular strategies, and circular
practices, so that value creation can be highlighted in terms of the potential benefits for
both managerial and policy projects.
Lastly, this work has certain limitations. Strict criteria have been applied during the
literature review process to refine article selection and analysis. Although this decision
was taken to better focus on the smart circular economy as an emergent phenomenon,
some (potentially relevant) articles dealing with sustainability and industry 4.0 may have
been overlooked. In addition, our analysis was limited to a pre-defined set of digital
technologies—namely, the IoT, big data and analytics, 3D printing, blockchain, and aug-
mented and virtual reality. These technologies have been selected on the basis of their
simultaneous academic relevance and implementation potential. Future studies should
consider the potential of other digital technologies (e.g., for the smart circular economy
paradigm). Lastly, our research mainly adopted a managerial perspective, focusing on the
functionalities enabled by digital technologies rather than on the technologies themselves.

Author Contributions: Conceptualization, G.B., F.A., D.C.A.P., and V.P.; methodology, G.B., F.A.,
D.C.A.P. and V.P.; validation, G.B., F.A., D.C.A.P. and V.P.; formal analysis, G.B.; investigation, G.B.;
data curation, G.B.; writing–original draft preparation, G.B.; writing–review and editing, G.B., F.A.,
D.C.A.P. and V.P.; visualization, G.B.; supervision, G.B., F.A., D.C.A.P. and V.P. All authors have read
and agreed to the published version of the manuscript.
Funding: This research was funded by the Research Council of Norway (Project no: 326087), by
Formas (Project no: 2018-01417), and by the Swedish Energy Agency (Project no: 52742-1).
Institutional Review Board Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
Sustainability 2022, 14, 4960 18 of 20

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