Industrial Transformation Roadmap for Digitalisation and Smart
Factories: The Danish SMEs Model
R. Addo-Tenkorang
1,*
, C. Møller
2,3
and K.-L. Chen
2
1
University of East London (UEL), Royal Docklands School of Business & Law, University Way, London, E16 2RD, U.K.
2
Aalborg University, Department of Materials and Production, Centre for Production,
Fibigerstræde 16, 9220 Aalborg, Denmark
3
Aarhus University, Department of Mechanical and Production Engineering, Katrinebjergvej 89, 8200 Aarhus, Denmark
Keywords: Digitalisation, Supply Chain Management (SCM), Industry 4.0, Small & Medium Enterprises (SMEs),
Internet of Things (IoT), Smart/Virtual Factory.
Abstract: Today only some sections of the supply chain are digitalized, but some companies are also already far with
Industry 4.0, where the virtual factory and the physical factory work closely together (digital twin). Industry
4.0, which started in Germany among the large OEMs, seems to have not resonated much with SMEs. There is
an imminent challenge of coming up with a feasible transformation roadmap which will resonate effectively
and efficiently with SEMs as they are the core backbone of every performing economy. This research
investigates Smart Factories/Industry 4.0 in the Danish SMEs model perspective. This research’s main
objectives are to develop a feasible roadmap in the form of a conceptual framework for easy industrial
transformation to the digitalizing and smart way of (doing things) developing products and/or services. This
research employs quantitative research methods such as surveys and interviews where applicable as well as a
literature review in the SMEs perspective. Previous research has shown that the digital evolution coined as
Industry 4.0 was started among large companies. However, this initial precedence has not resonated very
much with all-inclusive industrial evolution, especially within the SMEs perspective. The main industrial
implication will be the definition of a clear feasible roadmap for what this research terms as an industrial
transformation process - “digital change management process – Industry 4.0/Smart factory” in the industrial
SMEs perspective – the Danish Model. This research seeks to propose a conceptual smart factory roadmap in
an Industry 4.0 perspective, which could be adopted among manufacturing SMEs to effectively, and
efficiently transform their production operations. The Danish model perspective or angle of Industry 4.0.
1 INTRODUCTION
The world as we all know has seen three major
successive technological and industrial revolutions.
The Industrial Revolution first started in England at
the very end of the 18th century up until somewhere
towards the mid-19th century. It represented a radical
shift away from a more farm-based economy to a
more defined one by the introduction of mechanised
and/or mechanical production methods, which is also
known as mechanised farming. In the late 1960s
towards the beginning of the 20th century, the second
period of radical industrial transformation sets in
evolving from mechanised farming into industrial
production or manufacturing. Thus, the introduction
*
Corresponding author
of the birth of factories ushered the world into the
mass production of affordable consumer products.
This revolution also brought about the mass
utilisation of electronics and IT in industrial processes
in production and/or manufacturing processes, thus,
giving way to the new age of optimised and
automated production. The world now stands or is
experiencing the crescendo of the much-expected
fourth industrial revolution. This industrial revolution
promises to network and interconnect the worlds of
production and manufacturing employing network
interconnectivity into what is now known as the
“Internet of Things.” Thus, bringing about what is
now widely known as the “Industry 4.0” era
(Mckinsey Digital, 2015; Schuh, et al., 2017;
Henfridsson, et al., 2014).
144
Addo-Tenkorang, R., MÃÿller, C. and Chen, K.
Industrial Transformation Roadmap for Digitalisation and Smart Factories: The Danish SMEs Model.
DOI: 10.5220/0012094300003552
In Proceedings of the 20th International Conference on Smart Business Technologies (ICSBT 2023), pages 144-153
ISBN: 978-989-758-667-5; ISSN: 2184-772X
Copyright
c
 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Industry 4.0 or the fourth industrial revolution
serves as a platform for what is termed, “Smart
production.” Smart production, therefore, is a
production or manufacturing process which functions
as a completely interconnected and automated
manufacturing system. This Smart production
process or system enables and enhances a production
process that, enables intelligent ICT-based machines,
systems, technologies and interconnected networks in
a way that makes it capable of independent exchange
and response to executed information in order
automatically manage industrial production supply-
chain processes and activities. Earlier research on
Industry 4.0 indicates that the fourth industrial
revolution is unique to Germany where it first started
to pick shape. Germany, being the home of huge high-
tech automobile OEMs also puts them in the right
standing in terms of the initial financial capital-
intensive investment required. The cyber-physical
production systems (CPPS) required and the nature of
the fourth industrial revolution, consisting of smart
equipment or devices provide the enabling superior
ICT-enabled interconnectivity for a seamless
integration and networked production environment.
Because the fourth revolution presents a
decentralized intelligence platform that helps
facilitates intelligent cyber-physical systems or
objects to be independently processed and managed,
as well as integrated into real and virtual worlds,
which is also known as the “Digital/Virtual Twin”
(Henfridsson, et al., 2014). This presents a crucial
new aspect of the manufacturing and/or production
paradigm shift. Therefore, this is a very essential
industrial paradigm shift from a “centralized” to a
“decentralized” production system. Thus, presenting
the possibility and capability for industrial
transformational technological advancements. This
paradigm shift would; thus, enable industrial
production machinery to not only simply add value
and/or “processes” materials into finished products,
but also the product as physical objects configured in
a way to be able to communicate with the machinery
to tell it exactly what to do.
This kind of massive “Digital Change
Management – (DCM)” approach can only be
possible or initiated in any industrial organization
when effective awareness of especially the top
management is firmly secured as well as the
organizational employees who will contribute to its
success. Therefore, this article seeks to investigate
how SMEs may also transform their classical routine
production processes into a “Smart Factory” or smart
production by attempting to propose a simple
industrial transformational roadmap in the form of a
conceptual framework. The rest of the article would
be expanding into detail the attributes mapped up in
the conceptual framework proposed in this article as
a feasible industrial transformation roadmap into a
“Smart Factory” or “Smart Production” as follows:
Design/Approach initiative - awareness creation (case
study surveys), Determining factors, Implementation
plan and Smart Factory/SCM digitalization &
evaluation.
2 DESIGN/APPROACH
INITIATIVE
Having a strategy is an important aspect of any
successful business. However, the journey towards
digitalisation and Industry 4.0 is an uncertain path for
most companies, especially SMEs. Defining the right
strategy and ensuring the continuity of business is a
challenging task, which is only increasing in
complexity, as digitalisation is becoming a permanent
bullet point on the strategic agenda. Managers and
decision-makers have to consider external as well as
internal factors when defining their business strategy
and creating an implementation plan. Failure to do so
might have severe consequences for the company,
leading to loss of business and in the worst-case,
bankruptcy.
When implementing a strategy, managers and
decision-makers have to go through a lot of
considerations regarding internal as well as external
factors. External factors: on one hand, digitalization
efforts and the cost of investments in new digital
capabilities are continuously decreasing, which is
enabling SMEs to follow the trend and upgrade their
facilities and products. On the other hand,
competition is getting steeper, market trends are
shifting at a higher rate, and customers are becoming
more unpredictable, demanding better quality, faster
delivery, and cheaper prices. Internal factors:
identifying and setting the right objectives and
estimating technical feasibility, as well as executing
the strategies within the organisation based on the
needs of the organization (Schuh, et al., 2017).
Hence, the organizational strategy is an essential
part of the industrial transformation roadmap for
digitalisation and smart factories that SMEs should
not neglect (Mckinsey Digital, 2015; Schuh, et al.,
2017; Piccinini, et al., 2015). However, defining
strategic objectives related to digitalization might be
very challenging in itself and more so if a company
wishes to quantify and monitor the objectives. It
would be more beneficial to focus the company
Industrial Transformation Roadmap for Digitalisation and Smart Factories: The Danish SMEs Model
145

strategy on customer needs, market trends and
company vision and use digital technologies as a
means to achieve this. Additionally, it is equally
important to prepare the organization to deal with the
appertaining changes that will emerge as companies
focus on digital technologies and ensure
organizational buy-in.
Therefore, based on the above note it would be
imperative that the awareness of digitalizing industrial
SC processes is first sorted with the top management,
executives and/or CEOs of organizations. This is a
strategic top-down approach that would ideally work
with very significant industrial transformation within
the organizational operations setup.
This approach could not also be realized without
the entire work personnel on board the organizational
“digital change management (DCM)”
shift/movement. Furthermore, effective and deliberate
relevant stakeholders’ engagement of both customers
and suppliers is expected in a co-design initiative.
2.1 Awareness Creation Modes (Case
Study & Surveys)
A good awareness creation procedure mostly begins
with all of the relevant stakeholders coming together
for a common goal, agenda or vision. The main
purpose of awareness creation at the beginning of a
digital transformation agenda is to quickly mobilise
relevant and significantly transforming ideas about
the digital transformation agenda by usually
beginning with the top management team and then the
operational staff. Therefore, awareness creation in
this sense could be defined as a broadly organised
effort to change routine operational practices or
activities, policies or behaviours (Sayers, 2006).
Hence, a well-planned and orchestrated awareness
creation is arguably one that would most effectively
and efficiently seek to communicate to stakeholders
detailed and pragmatic information. Therefore, this
approach is about a particular mode of awareness
creation to a large variety of groups or people with
different backgrounds, skill sets, responsibilities and
levels of education or assimilation rates such as that
in manufacturing SMEs. On this note, this study
would adapt Robinson’s solution to identifying the
seven steps to social change or transformation
(Giorgadze, 2003) which include:
 Knowledge - knowing there is a problem, thus,
transforming legacy operational processes in a
more digitalized transformed approach Desire -
imagining a different future or
transformational change agenda
 Skills - knowing what to do to achieve that
expected future or transformational change
 Optimism - confidence or belief in success
 Facilitation - resources and support
infrastructure (top management support and
staff cooperation)
 Stimulation - a compelling stimulus that
promotes action (requisite skill-set training &
enhancement)
 Reinforcement - regular communications that
reinforce the original message or messages –
constant iteration of the digital change
management processes until expected
efficiency, effectiveness and productivity to
boost return on investment (ROI) is achieved.
Figure 1: The seven steps to social change or transformation
Source: (Giorgadze, 2003).
Figure 1 above, sequentially illustrates Robinson’s
seven steps to social change or transformation. Thus,
with the above steps to social/industrial change or
transformation in mind, this research seeks to employ
a qualitative approach of employing surveys and
interviews to collect and analyze the awareness
creation phase of this research.
3 DETERMINING FACTORS
The current vision concerning digital transformation
is represented by the progressive replacement of the
automation pyramid with a network of nodes. These
consist of automated or semi-automated services that
intercommunicate digitally (Jeschke, et al., 2017).
3.1 The Concept of a Digital Supply
Chain
The digital supply chain is defined by Porter and
Heppelmann (Porter and Heppelmann, 2014) as a
“system of systems” organization, that is meant to
support and orchestrate interactions between partners
at a global level (Bhargava, et al., 2013),
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synchronizing the different processes (Schmidt et al.,
2015). These capabilities are based on machine-
generated data, the interconnection between the
multiple supply chain players, large-scale decisions,
automation of business processes, and integration
across the supply chain through information sharing
(Wu, et al., 2016).
According to that, one of the key aspects of the
digital supply chain is represented by transparency
(Scrauf and Berttra, 2016). Within information
management, this is considered a synonym for
information transparency (Turilli and Floridi, 2009)
and is meant for information visibility across a
system. From a business point of view, this is
translated into the availability of information for
supporting decision-making processes (Winkler,
2000; Vaccaro, and Madsen, 2006; DiPPiazza, 2003;
Turilli and Floridi, 2009). The competitive
opportunities related to digital transformation
(Mckinsey Digital, 2015) and, therefore, to the
transition towards a digital supply chain are based on
the achievement and the use of transparency across it.
3.2 The Key Transformation Areas
Although this transformation has originated from a
technology agenda, both researchers and practitioners
identified multiple fundamental factors that are
orbiting around it and that has to be addressed as well
to support this transition process. This has been
defined as a progression of multiple complexity
stages (Kagermann, et al., 2013) which have been
proposed in multiple maturity models (Lanza, et al.,
2016; Leyh, et al., 2016; Lichtblau, et al., 2015;
Schumacher, et al., 2016). The investigation
regarding the transition across these maturity stages
highlighted the need for addressing several
determining factors to operationalize this
transformation. These factors have been analyzed and
summarized by (Colli, et al., 2018) in the “360 Digital
Maturity Assessment” in five dimensions. These are:
 Governance: clear company strategy, awareness
concerning new technologies, both top-down
and bottom-up innovation possibilities, lean
management for innovation projects
 Technology: physical and digital assets that
enable the generation, transmission, storage and
analysis of digital data (e.g. CNC machines,
getaways, cloud computing platforms) as well
as physical and digital assets that base their
functionalities on data (e.g. collaborative robots
or autonomous guided vehicles)
 Connectivity: infrastructure needed for
transmission inside the organization as well as
across the supply chain value creation network:
the ability to identify and capture value from
new technologies and available data (e.g.
business model shift towards the servitization
paradigm, machine self- reconfiguration due to
enabled communication between the product
and the machine, predictive maintenance
enabled by machine learning application on
collected data from assets)
 Competences: cultural mindset and skills for the
digital transformation (e.g. training and learning
culture) as well as for capturing value out of
digital technologies (e.g. competencies related
to the use of digital technologies)
Although these dimensions have been identified,
an investigation regarding how these factors affect the
digital transformation process and which
management practices have to be adopted to address
them still has to be performed.
4 IMPLEMENTATION PLAN
4.1 The Importance of an
Implementation Plan
The implementation plan in this study would serve
the purpose of translating a company’s strategic
vision into tangible goals on a tactical level and
specific steps to follow on an operational level. A
digitalization strategy for SMEs might not be as
extensive as one of a large enterprise; however, an
implementation plan might still be highly beneficial
for SMEs to consider. Due to the limited
implementation of new digital technologies and lack
of empirical data regarding pitfalls and common
mistakes, a strict implementation plan might not be
the best approach for SMEs.
An implementation plan for an SME should be
rather flexible and focus on the alignment between
decision-makers and production floor workers since
the workers will most likely play vast roles in
designing and implementing any new solutions.
Therefore, an implementation plan for an SME
should be brief and serve to answer questions such as
what, why and how. Answering these questions will
ensure alignment between a company’s strategic
vision and implemented solutions.
4.2 Following a Systematic Iterative
Process Model
Due to the many uncertainties around working with
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147

new technologies and the lack of knowledge
regarding the challenges that might occur along the
way: it might be highly beneficial to follow a
systematic iterative process that focuses on
continuous learning and improvements. On a macro
level, we suggest an implementation plan that
includes the four phases shown in Figure 2 below.
These four phases are, understand, define,
prototype and test, implement and standardise.
The authors have developed this model based on
the combination of the Design Thinking approach by
(Doorley, et al., 2018), which follows the four phases
of Empathize, Define, Ideate, Prototype, and Test as
well as lean principles, which highlights
standardization as an essential step in any new
implementations (Womack and Jones, 2003). The
suggested model for the implementation plan will
provide a systematic and holistic approach to
implementing new and untested digital solutions.
Figure 2: Four-phase plan for implementing new digital
solutions, inspired by Design- (Doorley, et al., 2018) and
Lean thinking (Womack and Jones, 2003).
On a micro level, (meaning the operational and
project management part), for the different tasks in
each of the four phases in the implementation plan,
suggest that following a simple Plan, Do, Check, Act
(PDCA) approach, could ensure an iterative process
(Andersen, 2007). The Plan phase focuses on defining
the what, why and how, thus this is in terms of the
approach or design initiative.
The Do phase focuses on following through with
the implementation. The Check phase focuses on
following up on the performed activities from the Do
phase. Finally, the Act phase serves to ensure that the
necessary actions are taken to adjust and improve, or
to standardize the solution in terms of demystifying
complexity and maximizing responsiveness into the
incremental digitalization transformational phase -
Smart Factory / SCM Digitizing Evaluation.
4.3 Incorporating Human Factors
Diaz, et al., 2016; estimates that the transition to
Industry 4.0 will demand human-centric design and
engineering philosophies that focus on enhancing and
augmenting the human workers' physical and
cognitive capabilities rather than unmanned
automated factories. Hence, such a statement
emphasizes the importance of considerations
regarding human factors and ergonomics and the
importance of accommodating the worker's well-
being.
While all companies are different and operate by
their cadence, we suggest that it would be highly
beneficial to also follow or get inspiration from
standards such as human-computer-interaction (HCI)
standards (BSI, 2010; BSI, 2016)), which deal with
Human Centred Design (HCD). In cases where the
implementation of new digital technologies affects
the roles and responsibilities of workers, it would be
beneficial to consider the following recommendations
as companies start anchoring in the implementation.
Kadir, et al., 2018; make the following
suggestions regarding working with collaborative
robots, although it is arguable that the same principles
might apply to other new digital technologies as well.
With the implementation of any new digital
technology, SMEs should strive to develop some sort
of Standard Operation Procedures (SOP) to highlight
the division of labour between workers and digital
technologies.
In addition to SOPs, formalizing a brief job
description for each worker might also be beneficial
in this regard. Such standardization will ensure
consistency and pave the way for continuous
improvements.
4.4 The Conceptual Framework for
Industrial Transformational
Roadmap: The Danish SME Model
The Denish local region of Aalborg has assigned
Aalborg University (AAU) to establish an ecosystem
around the AAU Smart Lab to support local SMEs
with information and activities that enable them to
identify and realise the potential of Industry 4.0 (I4.0)
in their particular context. Thus, the Innovation
Factory North (IFN) was founded to build a local
ecosystem of SMEs, technology suppliers, and R&D
institutions to develop I4.0 competencies (Møller, et
al., 2022b).
The approach enabled the qualified industries to
collaborate on Industry 4.0 awareness and innovation
in the IFN ecosystem. Hence, the digital
transformation roadmap towards Industry 4.0 is
corporate transformation with IT as an enabler and
strategic goal (Møller, et al., 2022b). Therefore, most
of the frameworks for industrial transformation are
primarily top-down approaches driven by a strong
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managerial vision and supported by large-scale
investments and enablement projects or programs as
illustrated in Figure 3 below. Although this approach
does not fit the local industry structure of Denish
manufacturing SMEs very well due to their low level
of digital maturity, the proposed conceptual
framework illustrated in Figure 3 below provides a
feasible digital transformation roadmap for these
Danish SMEs.
Figure 3: Industrial Transformation Roadmap – A
Conceptual Framework for Smart Factories.
Figure 3 above, illustrates the iteration sequence or
model adopted in this study for the conceptual
framework targeted for the Danish SMEs model, for
the digitalization of industrial SMEs’ transformation
roadmap agenda.
5 SMART FACTORY/ SCM
DIGITALIZATION &
EVALUATION
5.1 SME Manufacturing Firms Toward
Product-Service Offerings:
A Digitalisation Perspective
A product-centric manufacturing firm that wants to
achieve the vision of moving the value chain position
further downstream
to its end customers has to
transform. Thus the transformation toward the
product-service offering rather than the pure
products. Scholars argue that during this
transformation, organizations are likely to change
their strategy, operations and value chains,
technologies, people expertise and system integration
capabilities. The questions are WHAT is the
difference between this transformation era to the prior
industry revolutions? What is the lesson learnt from
the previous industrial revolutions?
Indeed, the business context of Industry 4.0 is far
more complex than anyone in previous history. A
“product” is not only produced for one single
functional usage purpose. A product thus, on the other
hand, also plays the role of a “bridge” towards a
business ecosystem. The paper outline below some
examples of Denmish Smart Factory SMEs that have
attempted to implement Smart Production processes
or aspects of it by adopting the digital transformation
roadmap(Møller, et al., 2022b): Maersk and the IBM
joint venture Tradelens is an example of a corporation
employing an Intelligent Supply Chain (Moller &
Maersk, 2019). Maersk has access to practically the
entire container logistics ecosystem via the Tradelens
platform and may benefit from a balanced demand
and supply. In another case, an SME changed its
function in the supply chain from Engineer-to-order
to Assembly-to-order by integrating the supply chain
with digital technology (Bejlegaard et al., 2021).
The integration of engineering activities across
the full lifecycle is referred to as virtual
manufacturing. Concurrent engineering, verification,
and validation of new goods or changes in products
or manufacturing processes are possible when
engineering operations are digitally linked (Addo-
Tenkorang, R., 2011). Vestas (Yidiz et al., 2021) is an
example of the possibilities of end-to-end digital
manufacturing. Vestas can teach employees virtually
using VR technology before the physical factory is
completed, therefore increasing the time to market.
Industry 4.0 is built on the collaboration of Smart
Factories across the whole manufacturing ecosystem
(Schou, et al., 2021).
In Industry 4.0 and Smart Production, an
empowered and agile organisation is critical. An
organisation can be enabled by instrumenting and
linking personnel at all levels, from the shop floor to
the boardroom, for optimal decision-making. This
necessitates the timely and appropriate degree of
information required for educated decision-making,
given in an actionable manner. Arla exemplifies how
an effective collaboration could empower an
organisation by decentralising access to analytical
data to support local data exploration and decision-
making (Asmussen et al., 2021).
Industrial Transformation Roadmap for Digitalisation and Smart Factories: The Danish SMEs Model
149

6 DIGITALIZATION &
EVALUATION
6.1 Demystifying Complexities and
Maximizing Responsiveness
To respond to and also be able to evaluate those five
determining dimensions (Colli, et al., 2018) in the
above-mentioned section, an agile project
management approach would be one of the promising
means. According to Brady and Davis, 2004, a good
model
of project capability-building is often
recognized to have two ways of complementary
approaches. They perceived that those firms,
equipped with two interacting levels of project
management are highly reaching competitive success.
On one hand, a bottom-up approach, called
‘project-led’ learning, is working cross-different
layers of the organization. It works from an
exploratory phase (e.g. new to technology) to a
lesson-learned phase (capture using experience) and
then to an equipped phase (the ability to implement
such new technology).
A top-down approach, on the other hand, called
‘business-led’ learning, is taken place to support and
lead the upcoming project activities with sufficient
resources and the right competencies; Figure 4 below,
gives a generic and simple illustration of these
contextual perspectives of what this study also terms
as digital change management (DCM). The idea of
running a complete project management circle creates
checking points to echo those five identified factors
toward the maturity of digitalization (Colli, et al.,
2018).
Figure 4: Contextual evaluation framework towards
digitalization (Colli, et al. 2018)
Further to the move for digitalization of industrial
production processes in smart production with
Industry 4.0, it is approached in an industry-specific
implementation process for SMEs; this has led the
agenda of the European Council (EC) to come up with
a new policy position on Industry 5.0 (Møller, et al.,
2022a).
The European Commission has positioned
Industry 5.0 as its transformative vision for Europe in
relation to Industry 4.0 as: “It complements the
existing Industry 4.0 approach by specifically putting
research and innovation at the service of the transition
to a sustainable, human-centric and resilient
European industry” (European Commission, 2021).
7 INDUSTRIAL IMPLICATIONS
Industrial implications of digital transformation, in
general, seem to pose some challenging
multidimensional trends for top management. SMEs
seem to be currently challenged with radically and
rapidly reshaping and transforming their enterprise
operations, which is thus, straining their existing
business operations to enable them to sustain their
competitiveness (Mckinsey Digital, 2015; Schuh, et
al., 2017; Piccinini, et al., 2015; Henfridsson, et al.,
2014).
Therefore, the main industrial implication
identified by this study is defining a clear feasible
roadmap for what this research terms an industrial
transformation process: which is coined in this
research as the “digital change management (DCM)
process – Industry 4.0/Smart factory” in the industrial
SMEs perspective – the Danish Model as illustrated
in Figure 3 above.
Thus, industrial digital transformation
technologies could be described as a digital-change
management process, as a combination of data/big
data, information, computing, communication and
connectivity or networked technologies. These
technologies would include cloud computing, big
data value-chain management, big data analytics, and
mobile and networking technologies (Bharadwaj, et
al., 2013).
Therefore, digital transformation technologies
provide SMEs with both open and flexible
operational environments that allow organizations to
break some of the traditional operational constraints.
These organizational constraints, together with
previously detached networks when effectively and
efficiently transformed by digitalization; fosters an
enabling environment for innovations to create new
customer experiences, relationships, and overall
organizational digital transformation (Lucas, et al.,
2013; Yoo, et al., 2012).
Current research trends on industrial digital
transformation and innovation have brought to bear
how the essence of the emergence of industrial digital
transformation technologies is bringing about a
paradigm shift in industrial production processes.
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This has enabled organizations to achieve major
operational efficiency and effectiveness by enabling
the creation of new business models or frameworks
(Fichman, et al., 2014). Furthermore, innovation
processes always seem unpredictable, and previous
research has outlined how inferior technologies win
market dominance because of higher adoption rates
and also the old looming threat of cyber security
issues with technology innovations. Therefore, this
could mean, that cheaper and inferior technologies,
will disrupt incumbent vendors’ technologies (
Møller,
et al., 2022a).
Leng et al., 2021, a measure to tackle this
cybersecurity issue in smart productions is the use of
blockchain technology. It is an innovative computing
paradigm that is recently revolutionizing the digital
world and bringing a new tool to the cybersecurity
and efficiency of systems (Ahram, et al., 2017). This
blockchain technology is a foundation for distributed
ledgers that offers transparent and decentralized
data/information; it is a mechanism for making
authenticated computational transactions in both
business and industry areas (Yuan and Wang, 2018).
The inherited characteristics of blockchain
technology as a cybersecurity measure would
enhance trust through transparency and traceability
within production/industrial transactions (Abeyratne
and Monfared, 2016).
8 ORIGINALITY & VALUE
In this study, the proposed industrial digital
transformation roadmap seeks to provide SMEs with
the unique advantage of enabling opportunities for
value creation from expanding profit pools – return-
on-investment (ROI), creating new revenue models
such as “servitization” within their operations
management.
This, therefore, affords them an exceptionally
enabling equal playing field for businesses in
accessing global markets’ digital initiatives. Thus,
possessing or equipping the SMEs with the enabling
potential to improve their business operations more
sustainably.
Therefore, this research given the potential
opportunities of digital transformation technologies
seeks to propose a conceptual smart factory roadmap
in an Industry 4.0 adopted by manufacturing SMEs to
transform their products effectively and efficiently
and/or servitization operations among the Danish
industrial SMEs.
9 CONCLUSION AND
RECOMMENDATION
The importance of realizing the collaborative force
and value of digital transformation technologies
cannot be overemphasized, given that digitalization
has a central role as a potential technological solution
for many of the challenges SMEs are confronted with
today.
Thus, driven by digital technologies, obligatory
role in today’s SMEs' operational activities, they must
be ready and adequately prepared to deal with
business transformations that are more progressive
incrementally but radical enough. This is to enable
smooth integration and interfacing with their existing
legacy systems than some of the known effects
reported on IT transformations in recent-past research
(e.g., Piccinini, et al., 2015).
Therefore, further study into this research will
look into further investigating in detail each of the
blocks in Figure 3 – the industrial transformation
conceptual roadmap. Also, some of the core
challenges and critical success factors associated with
them and in line with the industrial digital
transformation agenda among SMEs in Denmark
(The Danish model). This approach and/or study
would be among the first research to, systematically
investigate digitalization and/or digital
transformation among industrial SMEs. Digitalization
and digital transformation with the operational
processes of these SMEs have been radically initiated
here in Denmark already as compared to previous
studies available concerning the genesis of Industry
4.0 activities and operations among the rather huge
original equipment manufacturers (OEMs)
specifically in Germany (Adolph, et al. 2016; Møller,
et al., 2022a; Møller, et al., 2022b).
ACKNOWLEDGEMENTS
Manufacturing Academy of Denmark (MADE) SPIR
& Digital.
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