Published at : 27 Dec 2022
Volume : IJtech
Vol 13, No 7 (2022)
DOI : https://doi.org/10.14716/ijtech.v13i7.6193
Aleksandr Babkin | Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaia Street, 29, Saint Petersburg, 195251, Russia |
Elena Shkarupeta | Voronezh State Technical University, 20-letiia Oktiabria Street, 84, Voronezh, 394071, Russia |
Irina Kabasheva | Kazan (Volga region) Federal University, Kremlevskaya St., 18, Kazan, 420008, Russia |
Irina Rudaleva | Kazan (Volga region) Federal University, Kremlevskaya St., 18, Kazan, 420008, Russia |
Alexander Vicentiy | Putilov Institute for Informatics and Mathematical Modeling Kola Science Centre of the Russian Academy of Sciences, Apatity branch of Murmansk Arctic State University, Fersman St., 24a, Apatity, 18420 |
Industry
5.0 is an integral driving force for industrial development to overcome a
resurgent strategic drift. This solution is a perfect tool to ensure a
sustainable, human-centered, and resilient industry and encourage man-machine
collaboration within intelligent cyber-social systems. A complete shift to
Industry 5.0 is only feasible when industrial systems apply digital
strategizing to enhance digital development. That would invite technologies and
humans to facilitate all operational and customer dealings, significantly
increasing the rate of innovation. This research aims to articulate a
multi-perspective conceptual framework based on the premises of digital
development of industrial systems in the strategic drift to Industry 5.0. The
methodology implied in this research rests on an interview with industry
experts, a case study of digitalization leaders in 2021, extensive and
systematic literature review and scientometric analytical tools, content
analysis and foresight. In this paper, the authors reframe the concept of
digital strategy and consider it as a notion independent of digitalization
strategy and digital transformation strategy that is traditionally based on the
formation of digital thinking, implementation of digital behavior patterns, the
transformation of mindset, and strategic wisdom. As a result, a brand-new
perspective on Industry 5.0 is suggested –
Nooindustry 5.0. This digital development framework provides grounds for a
digital business strategy to advance and shapes a platform-operating model to
nurture the digital maturity of industrial systems. This research identifies
key strategies for the transformation of an industrial system into a bionic one
to sail through the current strategic drift. Further scientific work has to be
carried out in order to assess the impact and effects of digital development of
industrial systems while shifting to Industry 5.0.
Digital strategizing; Framework; Industrial system; Industry 5.0; Strategic drift
The
world has entered an era of revolutionary transformation. On the one hand, the
current crisis opens a window of opportunity for industrial systems to develop
via the implementation of digital technologies that can significantly boost
their competitiveness and performance. On the flip side, industrial systems are
going through a strategic drift caused by a significant number of risks that are
looming above the successful shift from
Industry 4.0 to Industry 5.0. Industrial systems have to deal with a whole
range of undermining challenges, including destruction or reframing of
international economic ties; sanctions and a subsequent lack of access to a
number of technological solutions; insufficient sovereignty of some industrial
sectors; higher prices for technologies and component parts; delayed
implications of support measures that took place in the Covid-pandemic;
In their earlier research (Babkin
et al., 2021a; Babkin et al., 2021b) the authors came to the conclusion
that Industry 4.0 is no driver to settle entrenched social tensions because it
seeks to optimize business models and economic thinking, which indeed generates
the above-mentioned threats and risks. A neo-concept of Industry 5.0 is
designed to supplement the digital development of industrial systems with more
meaningful and efficient cooperation between people, machines, and systems in a
digital environment.
2. Literature
Review
2.1. Industry 5.0
The “Industry 5.0” neo-concept was coined in 2015,
only four years after the advent of Industry 4.0. Since 2020, the scientific
community has been showing unprecedented interest in the topic of Industry 5.0.
It is often associated with extreme automation based on the Internet of Things
and smart industries. However, other approaches should also be mentioned. For
instance, (Özdemir & Hekim, 2018) see
the democratic production of knowledge based on big data analysis and symmetric
innovation as a key objective of Industry 5.0. In his turn (Nahavandi, 2019) believes that increasing
productivity without removing people from production poses severe problems for
the global industry. Figure 1 presents key definitions of Industry 5.0 provided
by existing scientific sources.
Industry 5.0 is designed to establish solid cooperation, not competition, between humans and machines. (Doyle-Kent & Kopacek, 2019) believe that Industry 5.0 contributes to a paradigm shift in industrial development in a way similar to the Fourth Industrial Revolution. On the contrary, (Rada, 2018) and (Babkin et al., 2022b) emphasize that Industry 5.0 does not operate as another industrial revolution. But is indeed an evolutionary addition to Industry 4.0 technologies, aimed at strengthening cooperation between humans and robots. In their turn, the works of (Fedorov et al., 2021a; Fedorov et al., 2021b) consider Industry 5.0 as a fundamental requirement for the design of neuro-digital ecosystems. The study by (Breque et al., 2021) presents Industry 5.0 as a tool for ensuring a sustainable, human-centered, and resilient industry. The main problem is that the management of many industrial systems does realize the potential value and prospects of Industry 5.0 but is still not ready to implement digital strategizing. That contradiction reveals a significant gap between mere awareness and implementation of Industry 5.0 solutions.
2.2. Digital strategizing
Adaptability to strategic drift that takes place in
the transition to Industry 5.0 requires new digital solutions and tools for
digital strategizing of industrial systems. That's why another aspect that is
vastly covered in scientific research is the development of digital strategies.
For instance, the works of (Zhuravlev &
Glukhov, 2021; Koroleva &
Kuratova, 2020; Albukhitan, 2020; Hess et al., 2016; Matt
et al., 2015) deal with strategizing of digital transformation
within economic systems. It is worth noting that the works of (Sasev, 2021; Ludwig & Stegmann, 2021; García-Esteban
et al., 2021) consider the strategy of digitalization of various
processes in general. At the same time, specific digital tools and technologies
of strategizing – digital twins and artificial intelligence – are considered in
the works of (Surovitskaya, 2021; Simchenko et al.,
2021). Scientists who are directly engaged in digital strategizing
research are represented primarily by (Morton et
al., 2022; Glukhov et al., 2022; Babkin et al., 2022a; Kalinin, 2021; Morton et al., 2020; Ruel et al., 2020; Chanias et al., 2019).
Figure 2 presents key definitions of digital strategizing. The main conceptual
disadvantage of many scientific works dedicated to strategizing digital
development is that they generate and exploit confusing terminology. For
example, such notions as digital strategy, the strategy of information systems,
digitalization strategy, and the strategy of digital transformation, are used
interchangeably.
Figure
2 Digital Strategizing. Key Definitions
A number of scientists observe digital strategy from a
rather narrow perspective, defining it as a business strategy of an enterprise
based on the use of digital technologies and information systems. For instance,
the United Nations Development Program of Digital
Strategy, 2022-2025 applies a broader approach, where the term
"digital" is applied both to the constantly evolving range of
technologies and to the transformation of the work environment that allows
people and organizations to innovate and progress using technology. Thus,
digital strategizing should be considered beyond the simple introduction of
digital technologies into the operations of decision-makers in industrial
systems.
This research aims to define a
multi-perspective conceptual framework based on the premises of digital
development of industrial systems that takes place under strategic drift on the
way to Industry 5.0. This research primarily focuses on industrial systems that
operate in conditions of adaptation to an advancing digital environment, and
apply the advantages of digital solutions and digital behavior patterns in
order to increase their competitiveness and overall efficiency. It is
important to address the following issues in a comprehensive manner:
1. What is the research gap in the neo-concepts of
Industry 5.0 and digital strategizing?
2. What are the basic constructs of digital
development of industrial systems in the conditions of strategic drift?
3. What does the framework for the digital development
of industrial systems in strategic drift include in the transition to Industry
5.0?
4. Can Industry 5.0 be viewed as a cybersocial
framework for the digital development of industrial systems in the conditions
of strategic drift?
5. What is the comprehensive approach on how to define
the concepts of digital strategy and digital strategizing that does not avoid ambiguity between these notions and other terms, such
as digitalization strategies or digital transformation?
6. What are the strategies for transforming the
industrial system into a bionic industrial system?
To address the first two issues, a systematic
literature review was conducted based on scientific cognition analysis and
synthesis. It included assessment and combining scientific data carried out with appropriate techniques and instruments, including quantitative and
qualitative ones. Th authors employed a standardized eight-step methodology for
an independent systematic literature review developed (Okoli,
2015) (Figure 3).
Figure 3 Standardized methodology for the systematic literature review (also called systematic review)
As for the methods of a quantitative assessment of digital development, the authors used clustering and scientometric tools (Figure 4). The Elsevier Research Intelligence (Scopus), and the VOSviewer (Visualizing scientific landscapes) – version 1.6.18, released on January 24, 2022 – were used as analytical tools. Of the total number of all search results received, 76 publications were deemed relevant and were further analyzed.
Figure
4 Methodological research
tools
The address to the third research issue was obtained
through an interview with industry experts. The current state of digital strategizing
in 20 industrial systems was analyzed (Almaz Group, Vyksa Steel Works, Tactical
Missiles Corporation, 3B-System Cooling, CHEAZ Group, UEC Saturn, Tonar
Machine–Building Plant, Cable factory "Expert cable", United Engine
Corporation, etc.), and the problems of their digital transformation in the
conditions of strategic drift in the transition to Industry 5.0 were
investigated. Based on the of case study of digitalization leaders in 2021, the
fourth issue was solved. In order to gain insight into the concepts of digital
strategy and digital strategizing, content analysis was applied. The address to
the last research issue was obtained on the basis of the foresight, which also
allows us to identify areas for further research.
The scientometric analysis of the Scopus database from
30/09/22 revealed 76 documents based on the keywords "digital" and
"strategizing". The initial signs of interest to the problems of
digital strategizing date back to 2005, followed by a significant increase in
the number of works on the topic. Logically enough, such dynamics go hand in
hand with a growing interest in Industry 5.0. The obtained information included
citation data, bibliographic information, a brief description and keywords,
information on funding, etc. Later on, all these findings were uploaded to
VOSviewer, which allowed the designing of an entire map based on bibliographic
data (Figure 5).
As a result of scientometric analysis, 129 keywords were identified and divided into 16 clusters. The main constructs of digital development of industrial systems in conditions of strategic drift (keywords with occurrences more than 1 (from 2 to 8)) include: strategizing, strategy formation, strategy practice, IS strategizing, digital strategy, digital transformation strategy; digitalization, digital transformation; digital innovation; digital technologies, big data, robotics, artificial intelligence, etc. Based on the results of clustering and defining key constructs, the authors have developed a framework for the digital development of industrial systems that face a strategic drift in their transition to Industry 5.0 (Figure 6). The developed framework for the digital development of industrial systems in the strategic drift of the Industry 5.0 shift allows to correlate the stages of digital strategizing with the stages of digital development, milestones of industrial revolutions and their corresponding objects and tools.
Figure
5
Map based on bibliographic data from 76 Scopus documents (by keywords
"digital" and "strategizing")
Figure
6
Framework for the digital development of industrial systems in the strategic
drift of the Industry 5.0 shift
The framework is expected to serve as a basis for a
multi-perspective concept of digital strategizing in industrial systems, which
will allow industrial systems management and decision-makers to design a
digital development strategy, as well as to form a platform-operating model to
increase the level of digital maturity (Kvint et
al., 2022; Agus et al., 2021; Bencsik,
2020; Lyukevich et al., 2020). Based on the framework
(Figure 6), the authors present Industry 5.0 as a Nooindustry 5.0, with
reference to the terms “noosphere” (Jaseckova et al., 2022),
and “nooeconomics” (Bodrunov, 2019). This
industry rests on the principles of justice and reason based on a new type of
cooperation – noo-cooperation (Babkin et al.,
2022b). Industry 5.0 is centered around intelligent cybersocial
ecosystems – "ecosystems of a new meta-level, evolving in the transition
from Industry 4.0 to Industry 5.0. They incorporate cybersocial values of
human-centricity, sustainability, and resilience; and are characterized by a
high level of hyperconvergence of cybernetic, socio-ecosystem, technological
and cognitive modalities aimed at the achievement of ethical social goals,
sustainable well-being of humanity and each individual" (Babkin et al., 2022a).
While shifting to Industry 5.0, industrial systems
need to form a digital strategizing system. By one, the authors consider a
range of interconnected elements that shape a certain unity focused on the
interaction between digital solutions and people with digital thinking. Such
interaction occurs at different levels of industrial systems in the processes
that form, transmit, implement, host, and support a digital strategy. The digital
strategy is considered as the utilization of digital solutions in
strategizing based on digital thinking combined with the activities of
decision-makers. Such an incorporating approach leads to the overall
transformation of how work processes are organized and allows industrial
systems to innovate using technologies that create differentiated value and
effective competition through the use of new business models.
It is extremely important to terminologically
distinguish the concepts of digital strategy, digitalization strategy, and
digital transformation strategy. As Figure 6 shows, digital strategy is a
concept of a higher "rank", along with such fundamental concepts, as
"digital development" and "digital thinking". It is digital
thinking precisely – based on the transformation of perspective on preparation,
adoption, and implementation of solutions – that distinguishes the digital
strategy from the "strategy of digital transformation", and
"digitalization strategy". Digital thinking should be based on
strategic wisdom (Kvint et al., 2021) and
digital behavior patterns. The authors suggest considering industrial systems
with a high level of digital development in the strategic drift of the Industry
5.0 shift as bionic. Bionic industrial systems based on digital strategizing
combine digital technologies with human capabilities within Industry 5.0. The
goal of it all is to transform operations that develop experience, customer
relationships, and efficiency by significantly increasing the pace of
innovation (Kvint et al., 2022).
Transformation of an industrial system into a bionic one is possible when it
rests on four strategies: significant investment in digital technologies, data,
and human potential; use of artificial intelligence as the basis for digital
transformation; introduction of a platform-operating model; convergence of
technologies and human capabilities based on the principles of justice and
reason within the framework of the Nooindustry 5.0 (Panteleeva
& Petrov, 2022; Geliskhanov
et al., 2018).
As a result of this research, the authors clarify the
current condition of digital development in industrial systems that find
themselves in a strategic drift on the way from Industry 4.0 to Industry 5.0.
Systematization of the existing pool of definitions for "Industry
5.0" and "digital strategizing" allowed identifying a research
gap and the spotting a terminological confusion and a narrow approach to the
definition of digital development strategies. The study reveals the integral
constructs of digital development of industrial systems in the conditions of
strategic drift, including: digital strategizing, digital transformation,
digitalization, digital technologies, digital transformation strategy, digital
strategy, etc. The authors developed a structural framework for the digital
development of industrial systems in the strategic drift of the Industry 5.0
shift. On the basis of bionic industrial systems with a high level of digital
development, the author's interpretation of Industry 5.0 boils down to the
concept of Nooindustry 5.0, shaped. The concept of digital strategy is
terminologically separated from the concepts of digitalization strategy and digital
transformation strategy, based on the inclusion of such fundamentals as digital
thinking, mindset transformation, digital behavior patterns, and strategic
wisdom. Strategies for an industrial system to transform into a bionic one were
also proposed. The limitations of the study are related to the sample size of
the survey of 20 industry experts, as well as the longevity of the analyzed
cases of digitalization leaders in 2021. Further research on the topic requires
a careful consideration of such issues as the impact and effects of digital
development under the strategic drift in the shift to Industry 5.0.
The research was carried out within the framework of
project No. 20-010-00942A of the Russian Foundation for Basic Research (2020-2022).
Agus, A.A., Yudoko, G., Mulyono, N.,
Imaniya, T., 2021. E-Commerce Performance, Digital Marketing Capability and
Supply Chain Capability within E-Commerce Platform: Longitudinal Study Before
and After COVID-19. International Journal of Technology. Volume 12(2),
pp. 360–370
Albukhitan, S., 2020. Developing Digital
Transformation Strategy for Manufacturing. Procedia computer science,
Volume 170, pp. 664–671
Babkin, A.V., Fedorov, A.A., Liberman,
I.V., Klachek, P.M., 2021a. Industry 5.0: Concept, Formation and Development. Russian
Journal of Industrial Economics, Volume 14(4), pp. 375–395
Babkin, A.V., Shkarupeta, E.V., Gileva,
T.A., Polozhentseva, Yu. S., Chen, L. Methodology for Assessing Digital
Maturity Gaps in Industrial Enterprises, 2022a. Modernization. Innovation.
Research, Volume 13(3), pp. 443–458
Babkin, A.V., Shkarupeta, E.V., Plotnikov,
V.A., 2021b. Intelligent Cyber-Social Ecosystem Industry 5.0: Concept, Essence,
Model. Russia's Economic Revival, Volume 70(4), pp. 39–62
Babkin, A.V., Shkarupeta, E.V., Plotnikov,
V.A., 2022b. Management of Cross-Sectoral Development Potential in Industry
5.0: Theory, Tools and Practical Applications. Russia's Economic Revival,
Volume 72(2), pp. 50–65
Bencsik, A., 2020. Challenges of Management
in the Digital Economy. International Journal of Technology. Volume
11(6), pp. 1275–1285
Bodrunov, S., 2019. Noonomics: The
Conceptual Basis of the New Development Paradigm. Journal of New Economy.
Volume 20(1), pp. 5–12
Breque, M., De Nul, L., Petridis, A., 2021.
Industry 5.0: Towards a Sustainable, Human-Centric and Resilient European
Industry. Luxembourg, LU: European Commission, Directorate-General for
Research and Innovation
Chanias, S., Myers, M.D., Hess, T., 2019.
Digital Transformation Strategy Making in Pre-Digital Organizations: The Case
of a Financial Services Provider. The Journal of Strategic Information
Systems, Volume 28(1), pp. 17–33
Doyle-Kent, M., Kopacek, P., 2019. Industry
5.0: Is The Manufacturing Industry On The Cusp Of A New Revolution? In: Proceedings of the International
Symposium for Production Research 2019. Springer, Cham, pp. 432–441
Fedorov, A. A., Koryagin, S. I., Liberman,
I. V., Klacek, P. M., 2021a. Industry 5.0: the Basics of Creating Neuro-Digital
Ecosystems. Digital Economy, Smart Innovation and Technology, pp. 106–108
Fedorov, A. A., Liberman, I. V., Koryagin,
S. I., Klacek, P. M., 2021b. Design Technology for Neuro-Digital Ecosystems to
Realize Industry 5.0. ?-Economy, Volume 14(3), pp. 19–39
García-Esteban, J.A., Curto, B., Moreno,
V., González-Martín, I., Revilla, I., Vivar-Quintana, A., 2018. A
Digitalization Strategy for Quality Control in Food Industry Based on
Artificial Intelligence Techniques. In:
IEEE 16th International Conference on Industrial Informatics (INDIN), pp. 221–226
Geliskhanov, I.Z., Yudina, T.N., Babkin,
A.V., 2018. Digital Platforms in the Economy: Essence, Models, Development
Trends. ?-Economy, Volume 11(6), pp. 22–36
Glukhov, V.V., Babkin, A.V., Shkarupeta,
E.V., 2022. Digital Strategizing of Industrial Systems based on Sustainable
Eco-Innovation and Circular Business Models in the Context of the Transition to
Industry 5.0. Economics and Management, Volume 28(10), pp. 1006–1020
Hess, T., Matt, C., Benlian, A., Wiesbock,
F., 2016. Options for Formulating a Digital Transformation Strategy. MIS
Quarterly Executive, Volume 15(2), pp. 123–139
Jase?ková, G., Konvit, M., Vartiak, L.,
2022. Vernadsky's Concept of The Noosphere and Its Reflection in Ethical and
Moral Values of Society. History of Science and Technology, Volume
12(2), pp. 231–248
Kalinin, A.R., 2021. Digital Strategizing of
Mining Enterprises. Property Relations in the Russian Federation, Volume
234(3), pp. 7–11
Koroleva, E., Kuratova, A., 2020. Higher
Education and Digitalization of the Economy: The Case of Russian Regions. International
Journal of Technology. Volume 11(6), pp. 1181–1190
Kvint, V.L., Babkin, A.V., Shkarupeta,
E.V., 2022. Strategizing of Forming a Platform Operating Model to Increase the
Level of Digital Maturity of Industrial Systems. Russian Journal of
Industrial Economics, Volume 15(3), pp. 249–261
Longo, F., Padovano, A., Umbrello, S.,
2020. Value-oriented and ethical technology engineering in industry 5.0: A
human-centric perspective for the design of the factory of the future. Applied
Sciences, Volume 10(12), pp. 4182
Ludwig, S., Stegmann, C., 2021.
Digitalization Strategy. The Digital Journey of Banking and Insurance,
Volume I, pp. 19–33
Lyukevich, I., Agranov, A., Lvova, N.,
Guzikova, L., 2020. Digital Experience: How to Find a Tool for Evaluating
Business Economic Risk. International Journal of Technology. Volume
11(6), pp. 1244–1254
Matt, C., Hess, T., Benlian, A., 2015.
Digital Transformation Strategies. Business & information systems
engineering, Volume 57(5), pp. 339–343
Morton, J., Amrollahi, A., Wilson, A.D.,
2022. Digital Strategizing: An Assessing Review, Definition, and Research
Agenda. The Journal of Strategic Information Systems, Volume 31(2), p.
101720
Morton, J., Wilson, A.D., Cooke L., 2020.
The Digital Work of Strategists: Using Open Strategy for Organizational
Transformation. The Journal of Strategic Information Systems, Volume
29(2), p. 101613
Nahavandi, S., 2019. Industry 5.0 – A
Human-Centric Solution. Sustainability, Volume 11(16), pp. 1–13
Okoli, C., 2015. A Guide to Conducting a
Standalone Systematic Literature Review. Communications of the Association
for Information Systems, Volume 37(1), p. 43
O?zdemir, V., Hekim, N., 2018. Birth of Industry
5.0: Making Sense of Big Data with Artificial Intelligence, “The Internet of
Things” and Next - Generation Technology Policy. Omics: a Journal of
Integrative Biology, Volume 22(1), pp. 65–76
Panteleeva, A.P., Petrov, S.V., 2022.
Improvement of Economic Analysis and Operational Analytics in the
Implementation of Digital Economy Technologies. In: Proceedings of
Higher Educational Institutions. Povolzhsky region. Social Sciences, Volume
2(62), pp. 200–209
Rada, M., 2018. Industry 5.0 – Evolution,
not Revolution. Available Online at: https://michael-rada.medium.com/industry-5-0-evolution-not-revolution-b4a7bdb3dfc1,
Accessed on October 29, 2022
Ruel, H., Rowlands, H., Njoku E., 2020.
Digital Business Strategizing: The Role of Leadership and Organizational
Learning. Competitiveness Review: An International Business Journal. Volume
31(1), pp. 145–161
Sasev, N.I., 2021. Theoretical and
Methodological Foundations of Strategic Trend Analysis in Sectoral
Strategizing. Models, Systems, Networks in Economics, Technology, Nature,
and Society, Volume 4, pp. 5–15
Simchenko, N.A., Filonov, V.I., Tsyohla,
S.Yu., 2021. Strategizing the Development of Economic Environment for the
Introduction of Digital Twins in Industry. Problems of Modern Economics,
Volume 2, pp. 31–35
Surovitskaya, G.?., 2021. The Potential of
End-To-End Digital Technologies for Improving Quality Management Systems. Models,
Systems, Networks in Economics, Technology, Nature and Society, Volume 3,
pp. 60–70
United Nations Development Programme.
Digital Strategy 2022-2025, 2020. Available Online at:
https://digitalstrategy.undp.org, Accessed on October 29, 2022
Zhuravlev, D.M., Glukhov, V.V., 2021.
Strategy of Digital Transformation of Economic Systems as a Driver of
Innovative Development. ?-Economy, Volume 14(2), pp. 7–21